What teams building AI features on CrewAI report, with every finding tied to its evidence.
Read the findingsPractitioner sentiment, all practitioners
−7 Mixed from 30 sources that take a side
How this figure is madeFrom 30 authors in 29 discussions. Build one pilot agent to measure the glue code and debugging time the framework adds.
Jan 2025 to Oct 2026.
55 sources from practitioners, by month and sentiment.
Speed to a first working crew is the most consistent praise. Runtime defects draw the most concerns, followed by control over what agents do once workflows grow and by defaults and dependencies, where every release now requires a ChromaDB version under a critical advisory.
Positive, mixed and negative sources
The score counts each source once, as the split does. See How the numbers work.
See the evidenceBelow: 2 praise themes, 5 concerns, 3 close to agreement and 1 disagreement.
Counted for All practitioners, from 55 sources. Change group
Every capability practitioners describe positively, ranked by how many sources say so. Open one to read who said it.
Counted for All practitioners.
Positive
Emmanuel Chukwu (Emagzimus), builder posting on X
Post on building a research and writing crewPost on X
Says CrewAI feels like managing a team; built a pipeline where a research agent searches the web and a content agent writes the blog post.
Mixed
sunnydachs, developer writing on dev.to
I built the same agent in Strands, LangGraph, and CrewAI and recorded every LLM callPersonal blog post, dev.to
CrewAI produced byte-identical output across runs and was quick to prototype, but its install weighed 699 MB across 142 packages against 71 MB for LangGraph.
Mixed
jamilxt, dev.to author
LangGraph vs CrewAI vs OpenAI Agents SDK: Picking Your Agent Framework in 2026dev.to post
Finds CrewAI the shortest route to a working multi-agent prototype, citing published comparisons that put one under 20 lines of Python.
Mixed
ashg2099, developer writing on dev.to
Why I'm Betting on CrewAI for Multi-Agent Orchestration (And Where It Falls Short)Personal blog post, dev.to
Bets on CrewAI for research, analysis, and content pipelines with explicit roles and tasks, and lists token costs that compound with every agent call as a real limitation.
Mixed
Kacper Wlodarczyk, AI engineer at Vstorm
One Chat App, 4 AI Frameworks ComparedCompany engineering blog
CrewAI's version of the app took about 420 lines against about 160 for Pydantic AI, with research and writer roles out of the box, but needed a background thread for streaming and run_in_executor for async.
Positive
kingabzpro, Reddit poster in r/AI_Agents
I built an open-source app where LLM agents debate a stock before a manager agent decides the tradeReddit post
Runs analyst, bull, bear, judge, and manager agents locally on FastAPI and CrewAI with any OpenAI-compatible API; a first session on DeepSeek costs about US$0.01.
Mixed
Shaam (shaam_ai), dev.to author
Agentic AI Frameworks Compared 2026: LangGraph Winsdev.to post
Names CrewAI the best start for beginners because role-based crews map onto how people describe work, lists coarser control, moving abstractions and docs churn as the cost, and advises testing run latency early on complex crews.
"A: CrewAI, because role-based crews map onto how people already describe work."
Mixed
Apart-Currency7380, Reddit commenter in r/LangChain
Comment on: LangGraph or CrewAI for agent handoffsReddit comment
CrewAI feels more natural for role-based workflows, but LangGraph's explicit state, checkpoints, and retries make complex handoffs easier once context grows.
Mixed
Jangwook Kim, dev.to author
AI Agent Frameworks Compared 2026: LangGraph vs CrewAI vs OpenAI SDKdev.to post
Rates CrewAI the fastest of six frameworks from idea to working prototype, and finds its role-playing abstraction harder to predict and debug in production, because agents make their own delegation decisions.
"Simple agent patterns require significantly more code in LangGraph than in frameworks designed for rapid prototyping."
Positive
Thoughtworks, Technology Radar volume 32
CrewAI, Technology Radar (Assess)Company technology publication
Thoughtworks placed CrewAI in Assess after using it several times on production problems, from validating promotion codes to investigating transaction failures and customer support queries.
GILD's fact checks, which don't count as sources
Checked Oct 28, 2026.CrewAI documents Crews as teams of autonomous agents that collaborate on tasks, inside Flows that manage state and control execution. CrewAI introduction
Open them in the recordCounted for All practitioners.
Positive
kingabzpro, Reddit poster in r/AI_Agents
I built an open-source app where LLM agents debate a stock before a manager agent decides the tradeReddit post
Runs analyst, bull, bear, judge, and manager agents locally on FastAPI and CrewAI with any OpenAI-compatible API; a first session on DeepSeek costs about US$0.01.
Mixed
Carlos Matias Baglieri, founder of FACTA
Post on graph engineering in production multi-agent buildsPost on X
Builds production multi-agent systems on CrewAI, LangGraph, and Agno, and says orchestration structure with human oversight is what keeps dozens of agents under control.
Positive
stockanalyst987, Hacker News commenter
Comment on: Show HN, RiskKernel, kill -9 an AI agent and resume it without paying twiceHacker News comment
Runs an agentic system built on CrewAI and planned to try a tool because it supports CrewAI.
Positive
matbanik, Hacker News commenter
Comment on: building agent workflows across coding agentsHacker News comment
Tests agent instructions in OpenCode, then ports the logic into LangGraph or CrewAI on Amazon Bedrock AgentCore, which takes about an afternoon to set up for production and then runs with little intervention.
"…port the agent logic into a framework like LangGraph or CrewAI and run everything on Amazon Bedrock AgentCore."
Positive
sherwin27, Hacker News commenter who contributed tools to CrewAI
Comment on: I added native time awareness to CrewAI to fix LLM date hallucinationsHacker News comment
Runs agents in production and contributed a TimeAwarenessTool and an IDGenerationTool to the core CrewAI repository to fix date hallucination and support log tracing.
Positive
Thoughtworks, Technology Radar volume 32
CrewAI, Technology Radar (Assess)Company technology publication
Thoughtworks placed CrewAI in Assess after using it several times on production problems, from validating promotion codes to investigating transaction failures and customer support queries.
Positive
dabe19, Hacker News commenter
Comment on: Ask HN, open-source AI agents building platform?Hacker News comment
Runs the crewAI library with ChromaDB and local Ollama models, and had to customize CrewAI's RAG tool to work with them; likes the class setup for building fully custom tools.
GILD's fact checks, which don't count as sources
Checked Oct 28, 2026.CrewAI AMP deploys crews and flows to managed infrastructure behind a REST API, and Enterprise runs on CrewAI cloud, a dedicated VPC, or the customer's infrastructure. CrewAI pricing
Checked Oct 28, 2026.Self-hosted AMP deployments ship logs to Datadog through the Datadog Agent or Datadog's OTLP intake, and CrewAI provides a ready-made operations dashboard for the integration. CrewAI AMP docs: Datadog integration
Open them in the recordEvery concern practitioners raise, most raised first.
Counted for All practitioners.
No opinion stated
Yifan Xiong (yifanxiong272), GitHub user filing an issue
Two agents set up at the same time can fail with RuntimeError: dictionary changed size during iterationGitHub issue
A flow class builds and caches its definition without a lock on first use, so two instances created at once can crash.
No opinion stated
ssshr-66, GitHub user filing an issue
A failed task can be skipped after checkpoint restore because its output remains setGitHub issue
When a task's output file write fails, the checkpoint still stores its output, and a restore can skip the failed task as if it completed.
No opinion stated
Wilson0511, GitHub user filing an issue
UploadCache sync wrappers deadlock 30s inside a running event loopGitHub issue
Every synchronous upload-cache call made inside a running event loop froze for 30 seconds and then failed with a bare timeout.
Negative
yiddo_bhushan, operations at Shogo, one of the eight platforms tested
Ran one build on eight agent platforms. Two finished.Reddit post
CrewAI and LangGraph both reported a Slack integration as connected and delivered nothing, with no error and nothing in the channel.
Mixed
Lucas Kim, AI/ML engineer and consultant whose GitHub profile lists AWS
GPT-6 Sol and Luna agents with tools worked through Bedrock, but every GPT-6 Astra agent with a tool failed with a 400, because CrewAI's retry sent a reasoning setting Astra rejects. Setting the Responses API worked.
No opinion stated
Rohit Kanithi (Rohitkanithi), GitHub user filing an issue
LanceDBStorage.delete() ignores scope/older_than filters and causes accidental mass deletionGitHub issue
Memory delete ignored scope and age filters in some cases and removed records outside the requested scope.
No opinion stated
suqinghen, GitHub user filing an issue
Memoized CrewBase methods retain per-instance Agent/Task/Crew in global cacheGitHub issue
Creating a crew per request left every Agent, Task, and Crew object in a module-level cache, so process memory grew with request count.
No opinion stated
Jucelio Quentino (jquentino-ambev), engineer at AB InBev filing an issue
Agent.kickoff_async guardrail retry calls sync invoke inside event loopGitHub issue
When a guardrail rejected an async agent's first output, the retry ran through the synchronous path and passed a coroutine on as the result, crashing the run.
No opinion stated
Joaquin DG (JoaquinDG), GitHub user filing an issue
Truncated responses are detected in the Bedrock provider onlyGitHub issue
Only the Bedrock provider flagged responses cut off at the token limit; other providers passed truncated output on as if complete.
No opinion stated
Thomas Connally (tcconnally), GitHub user filing an issue
Tool exceptions are caught and replaced with generic error messagesGitHub issue
CrewAI replaced tool exceptions with a generic error string and dropped the type, message, and traceback, so the cause of a failure could not be found.
GILD's fact checks, which don't count as sources
Checked Oct 28, 2026.crewai 1.15.32 shipped on October 27, 2026, the fifth release between October 14 and October 27, so pin a version and retest on each upgrade. CrewAI releases on GitHub
Open them in the recordCounted for All practitioners.
Mixed
Shaam (shaam_ai), dev.to author
Agentic AI Frameworks Compared 2026: LangGraph Winsdev.to post
Names CrewAI the best start for beginners because role-based crews map onto how people describe work, lists coarser control, moving abstractions and docs churn as the cost, and advises testing run latency early on complex crews.
"A: CrewAI, because role-based crews map onto how people already describe work."
Mixed
windexh8er, Hacker News commenter
Comment on: An Accidental BlackboardHacker News comment
Left to work it out among themselves, CrewAI agents collaborate awkwardly; defining coordination in the initial spec helps, though agents still drift from it.
Negative
Rafael Asor, author of the attenu-guard tool-gating library
I delegated a review in CrewAI. The reviewer ran an export tool the orchestrator never had.Personal blog post, dev.to
With allow_delegation=True, an orchestrator holding only a query tool delegated to a coworker that then ran an export tool the orchestrator never had.
Mixed
Jangwook Kim, dev.to author
AI Agent Frameworks Compared 2026: LangGraph vs CrewAI vs OpenAI SDKdev.to post
Rates CrewAI the fastest of six frameworks from idea to working prototype, and finds its role-playing abstraction harder to predict and debug in production, because agents make their own delegation decisions.
"Simple agent patterns require significantly more code in LangGraph than in frameworks designed for rapid prototyping."
Mixed
dsteel, Hacker News commenter whose team runs 14 AI agents
Comment on: How many products does Microsoft have named 'Copilot'?Hacker News comment
Says CrewAI, LangGraph, and similar frameworks solve how agents pass data but not which agent has authority over which domain or what happens when two agents disagree.
Mixed
Apart-Currency7380, Reddit commenter in r/LangChain
Comment on: LangGraph or CrewAI for agent handoffsReddit comment
CrewAI feels more natural for role-based workflows, but LangGraph's explicit state, checkpoints, and retries make complex handoffs easier once context grows.
Mixed
Kacper Wlodarczyk, AI engineer at Vstorm
One Chat App, 4 AI Frameworks ComparedCompany engineering blog
CrewAI's version of the app took about 420 lines against about 160 for Pydantic AI, with research and writer roles out of the box, but needed a background thread for streaming and run_in_executor for async.
No opinion stated
redvelvets, GitHub user filing an issue
Agent does not actually invoke tools, only simulates tool usage with fabricated outputGitHub issue
The agent wrote a plausible Thought, Action, Observation trace while never running the search tool; the model invented the observation.
Negative
nickwatson, Hacker News commenter building a research tool
Comment on: Show HN, Cleverb.ee, an open-source agent that writes a cited research reportHacker News comment
Rebuilt the research tool with CrewAI but found it limiting, and was rebuilding it again on AutoGen.
GILD's fact checks, which don't count as sources
Checked Oct 28, 2026.Flows add start, listen, and router steps and @persist state, so code decides which crew runs next. Flows
Open them in the recordCounted for All practitioners.
No opinion stated
axelgbl, GitHub user filing an issue
input_files (PDFFile) are passed as base64 via read_file tool, causing context overflowGitHub issue
PDF inputs reached the agent as base64 text through the read_file tool where native file inputs were expected, overflowing the context.
No opinion stated
Hamza-BinRiaz, GitHub user filing an issue
cache_breakpoint injected into messages for non-Anthropic providersGitHub issue
A cache_breakpoint flag meant for Anthropic was sent to every provider, and Groq and other OpenAI-compatible APIs rejected the requests.
Negative
Acacian, Hacker News commenter and author of the aegis guardrail library
Comment on: Show HN, I tested 11 AI frameworks for basic securityHacker News comment
Found no runtime injection detection, PII masking, or audit trail in 11 frameworks including CrewAI, and wrote a layer that patches them.
Mixed
eoskx, Hacker News commenter
Comment on: Tell HN, Litellm 1.82.7 and 1.82.8 on PyPI are compromisedHacker News comment
Pointed out that CrewAI imports LiteLLM directly and falls back to it when the OpenAI, Anthropic, and other provider SDKs are not installed.
Negative
mathis-l, Hacker News commenter
Comment on: Tell HN, Litellm 1.82.7 and 1.82.8 on PyPI are compromisedHacker News comment
Noted that CrewAI pinned LiteLLM to 1.82.6, the last good version, with a commit message that did not mention the compromise, and asked why users were not warned.
No opinion stated
IbrahimCanKALYA, GitHub user filing an issue
How can disable tracing prompt?GitHub issue
A tracing prompt added about 20 seconds to each run and kept appearing after setting tracing=False and CREWAI_TRACING_ENABLED=false.
No opinion stated
fzozyurt, GitHub user filing an issue
Even though I turned off the telemetry feature, telemetry is still being sentGitHub issue
Set CREWAI_DISABLE_TELEMETRY to true as the docs describe and still saw telemetry sent.
Mixed
sunnydachs, developer writing on dev.to
I built the same agent in Strands, LangGraph, and CrewAI and recorded every LLM callPersonal blog post, dev.to
CrewAI produced byte-identical output across runs and was quick to prototype, but its install weighed 699 MB across 142 packages against 71 MB for LangGraph.
No opinion stated
DipakBundheliya, GitHub user filing an issue
Tool Called Multiple Times in CrewAI v0.121.0GitHub issue
After upgrading to 0.121.0, a tool ran several times within one task although the first call succeeded; 0.120.0 called it once.
GILD's fact checks, which don't count as sources
Checked Oct 28, 2026.Anonymous telemetry is on by default. CREWAI_DISABLE_TELEMETRY or OTEL_SDK_DISABLED turns it off, and AMP tracing needs CREWAI_TRACING_ENABLED=false separately. Telemetry
Checked Oct 28, 2026.CrewAI's trust center lists a SOC 2 Type 2 report from June 2026, a HIPAA audit report, and data retention procedures, each released on request. CrewAI Trust Center
Open them in the recordCounted for All practitioners.
No opinion stated
r14dd, GitHub user filing an issue
Bedrock prompt_tokens excludes cache reads and writes, unlike other native providersGitHub issue
For a call with 1,200 prompt tokens, 1,000 of them cache reads, the Bedrock provider reported 200 prompt tokens while other providers reported 1,200.
No opinion stated
giskard09, GitHub user filing an issue
ToolUsage retries a failed tool call twice per outer attempt, not onceGitHub issue
A failed tool call is retried inside each outer attempt as well as by the outer loop, so a failing tool runs more often than the retry setting suggests.
No opinion stated
parthiban-sivakumar, GitHub user filing an issue
crew.usage_metrics multiplies token usage by the number of agents sharing an LLM instanceGitHub issue
With two agents sharing one LLM instance, crew.usage_metrics reported 310 tokens for a run that used 155, double the real count.
Negative
wartzarbee, developer writing a cost-audit series on dev.to
CrewAI's quadratic context problem: why a 5-agent crew costs 6x more than you expectPersonal blog post, dev.to
With default context passing, each task in a sequential crew re-sends earlier outputs, so a five-agent crew uses about six times the tokens of isolated tasks; scoping the context parameter fixes it.
No opinion stated
Devasy, GitHub user filing an issue
Token tracking race condition in threading-based async_executionGitHub issue
Per-task token tracking captured counts before tasks ran in parallel threads, so concurrent tasks were credited each other's tokens.
Mixed
ashg2099, developer writing on dev.to
Why I'm Betting on CrewAI for Multi-Agent Orchestration (And Where It Falls Short)Personal blog post, dev.to
Bets on CrewAI for research, analysis, and content pipelines with explicit roles and tasks, and lists token costs that compound with every agent call as a real limitation.
No opinion stated
axelgbl, GitHub user filing an issue
input_files (PDFFile) are passed as base64 via read_file tool, causing context overflowGitHub issue
PDF inputs reached the agent as base64 text through the read_file tool where native file inputs were expected, overflowing the context.
GILD's fact checks, which don't count as sources
Checked Oct 28, 2026.CrewAI AMP lists a usage dashboard with token counts on both Basic and Enterprise. CrewAI pricing
Open them in the recordCounted for All practitioners.
Mixed
frogscooper, AI engineer posting on X
Post on once, an idempotency library for agent tool callsPost on X
Built once, a Python library that keys each agent tool call so retries do not repeat paid calls, with support for CrewAI and other frameworks.
No opinion stated
Thomas Connally (tcconnally), GitHub user filing an issue
Tool exceptions are caught and replaced with generic error messagesGitHub issue
CrewAI replaced tool exceptions with a generic error string and dropped the type, message, and traceback, so the cause of a failure could not be found.
No opinion stated
azender1, GitHub user filing an issue
Tool re-execution on task retry has no idempotency guardGitHub issue
When a task is retried, every tool that already ran runs again, with no way to detect a completed call, so payments, emails, or trades can repeat.
No opinion stated
redvelvets, GitHub user filing an issue
Agent does not actually invoke tools, only simulates tool usage with fabricated outputGitHub issue
The agent wrote a plausible Thought, Action, Observation trace while never running the search tool; the model invented the observation.
No opinion stated
DipakBundheliya, GitHub user filing an issue
Tool Called Multiple Times in CrewAI v0.121.0GitHub issue
After upgrading to 0.121.0, a tool ran several times within one task although the first call succeeded; 0.120.0 called it once.
No opinion stated
giskard09, GitHub user filing an issue
ToolUsage retries a failed tool call twice per outer attempt, not onceGitHub issue
A failed tool call is retried inside each outer attempt as well as by the outer loop, so a failing tool runs more often than the retry setting suggests.
Negative
Rafael Asor, author of the attenu-guard tool-gating library
I delegated a review in CrewAI. The reviewer ran an export tool the orchestrator never had.Personal blog post, dev.to
With allow_delegation=True, an orchestrator holding only a query tool delegated to a coworker that then ran an export tool the orchestrator never had.
GILD's fact checks, which don't count as sources
Checked Oct 28, 2026.On restore from a checkpoint, CrewAI skips completed tasks and reruns the rest, so a tool inside an unfinished task runs again. Checkpointing
Checked Oct 28, 2026.CrewAI documents MCP servers as agent tools, through the crewai-tools library or the mcps field on an agent. CrewAI docs: MCP servers as tools
Open them in the recordStatements this group's sources agree on, then the ones close to agreement.
Close to agreement: each needs 11 supporting sources
CrewAI's token counts and retry behavior need checking against the provider's bill before production.
9 supporting sourcesCrewAI gets a role-based multi-agent prototype working faster than graph frameworks.
8 supporting sourcesAs workflows grow, teams want explicit state and control that role-based crews do not give, and some rebuild in LangGraph or their own code.
8 supporting sourcesQuestions the sources split on, with the count on each side.
Evidence remains split
Kept CrewAI, 7 sources
Thoughtworks, a founder running production builds, and individual builders keep crews running on real work, locally, in a service, or on Amazon Bedrock AgentCore.
Moved to other code, 5 sources
Others moved to AutoGen, Spring AI, a C++ framework, or a small framework of their own, citing limits, learning curve, and speed.
The three groups, then every practitioner by the context they work in, and how emphasis changes with scale.
Three groups drawn from the same sources. Choose a group to select whose experience counts. Within that group, each author counts once in the practitioner sentiment, with their latest view. Signals open on All practitioners. Teams and leaders have 4 accounts; GILD prints their sentiment from 20.
11 sources. Company teams and founders describe where CrewAI ran in their work and where its persistence and control stopped.
44 sources. Individual builders describe crews they prototyped, the bugs they filed, and the token and tool behavior they had to work around.
55 sources. These accounts combine company publications with solo developers, from local setups on one PC to services that create a crew per request.
55 sources from practitioners, by the context they work in. Filled rows count for this group.
Emphasizes Prototype speed, tool retries, and token counts
Emphasizes Authority between agents once a team runs many of them
Emphasizes Client production work, async defects in company use, and EpicStaff's and Browserbase's removals
Emphasizes Durability and human oversight in production builds
What changes with scale. Individual builders praise how quickly a role-based crew comes together and file most of the defects. Named companies appear as Thoughtworks' client work, an AB InBev engineer's bug report, engineering posts from Diagrid and Vstorm, and pull requests in which EpicStaff, Browserbase and Headroom removed CrewAI. Company-wide rollouts at PwC, Gelato and IBM Consulting appear only in CrewAI's own case studies.
Where this group's sources were published.
Counted for All practitioners, from 55 sources. Change group
69 sources for this group, 14 of them documentation
Earlier evidence remains when it still applies. Records tied to issues GitHub shows closed carry Needs a recheck.
See sources by originWho each source is, how it knows, whether it still applies and what it counts toward.
Newest first, on its own page. Every count above opens its sources there.
Read all 69 sourcesAbout this read
A running review of what teams building AI features on CrewAI report, from individual builders to technical leaders. Each finding links to its sources, and each conflict shows both sides.
Counts cover only the sources GILD reviewed.
Choose a group to select whose experience counts. Within that group, each author counts once in the practitioner sentiment, with their latest view. GILD files each source in a group from how the account describes its author. A role or employer marked self-described is what the source states about themselves. Documentation checks facts for every group and never counts toward sentiment.
A source's date and whether it still applies are separate: a recent post can describe an old version, and an old one can still hold.
Flagged for a recheck, of the sources that take a side: teams and leaders 1 of 4, individual builders 0 of 26, all practitioners 1 of 30.
Each row opens its sources for the group you are reading.
| Finding | Teams and technical leaders | Individual builders | All practitioners | Sources |
|---|---|---|---|---|
| Current readCurrent sentiment | 1 positive, 3 mixed, 0 negative | 6 positive, 11 mixed, 9 negative | 7 positive, 14 mixed, 9 negative | Sources |
| PraiseFast to a Working Crew | 2 of 2 positive (under the minimum) | 8 of 8 positive | 10 of 10 positive | Sources |
| PraiseCrews in Real Work | 2 of 2 positive (under the minimum) | 5 of 5 positive | 7 of 7 positive | Sources |
| ConcernCoarse Control Over Agents | 2 of 2 raise it (under the minimum) | 7 of 7 raise it | 9 of 9 raise it | Sources |
| ConcernToken Burn & Usage Accounting | 0 of 0 raise it (under the minimum) | 7 of 7 raise it | 7 of 7 raise it | Sources |
| ConcernTools That Run Twice or Not at All | 0 of 0 raise it (under the minimum) | 7 of 7 raise it | 7 of 7 raise it | Sources |
| ConcernDefaults, Telemetry & Dependencies | 0 of 0 raise it (under the minimum) | 9 of 9 raise it | 9 of 9 raise it | Sources |
| ConcernAsync, Memory & Checkpoint Defects | 1 of 1 raise it (under the minimum) | 9 of 9 raise it | 10 of 10 raise it | Sources |
| ConsensusFastest route to a crew | 2 supporting (under the minimum) | 6 supporting (below threshold) | 8 supporting (below threshold) | Sources |
| ConsensusState matters more as work grows | 2 supporting (under the minimum) | 6 supporting (below threshold) | 8 supporting (below threshold) | Sources |
| ConsensusCheck the meter yourself | 0 supporting (under the minimum) | 9 supporting | 9 supporting (below threshold) | Sources |
| DisagreementOnce a team has built on CrewAI, does it keep it or move on? | Kept CrewAI 2, Moved to other code 0 (under the minimum) | Kept CrewAI 5, Moved to other code 5 | Kept CrewAI 7, Moved to other code 5 | Sources |
| Current readEvidence mix | 25 sources | 58 sources | 69 sources | Sources |
GILD's checks of claims against official documentation, kept apart from the source counts.
