“That command
is out of date.”
Your agent follows an old setup guide. An engineer has to step in before useful work can start. We compare that guidance with the current configuration.
OUTDATED INSTRUCTIONSFOR TEAMS ALREADY USING AI CODING AGENTS
RepoChicken.
Same AI mistakes.
More rework.
Your engineers should not have to explain the same project rules in every coding session.
We audit the instructions behind your coding agents and give your team a prioritized fix plan, with evidence for every finding.
One focused engagement. No software subscription.
THE SCOPE1 codebase. Up to 3 workflows.
WHAT YOU GETFindings. Priorities. A fix plan.
THE PILOT$2,500 USD / one time
01 / THE REWORK YOU RECOGNIZE
Your team knows.
Your agents miss it.
Outdated commands. Ignored conventions. The same explanations in every session. We check whether the instructions behind those mistakes match your codebase.
“That command
“We don't build
it that way.”
The code looks plausible but ignores your team's conventions. We look for missing, buried, or contradictory project rules.
MISSED PROJECT RULES“I've explained
this before.”
Each session starts with the same explanation. We check whether those project rules are recorded, easy to find, and consistent.
REPEATED EXPLANATIONSNot every AI mistake is an instruction problem. We show what the evidence supports and what needs further testing.
02 / SEE WHAT YOU WOULD RECEIVE
A finding.
A reason. A next step.
Explore an illustrative example of the report format. Your audit would connect each finding to your codebase, explain why it matters, and give your engineers a practical next step.
Read the example report
RepoChicken.REPORT FORMAT
ILLUSTRATIVE EXAMPLE
From repeated correction
to a clear next step.
Example 01 / Outdated setup instructions
- The mismatch
- The guide names a command that the configuration no longer defines.
- The recommendation
- Update the guide and remove conflicting instructions.
- The acceptance check
- Verify the documented command in an agreed environment.
EXAMPLE 01 / OUTDATED COMMANDSILLUSTRATIVE
The guide sends your agent down a dead end.
Imagine a setup guide that still names a retired command. Your engineer has to correct the agent before it can get started.
Example mismatch / fictional snippets
Setup guide: npm run dev
Configuration: "start": "vite"- Suggested change
- Update the command and remove conflicting setup guidance.
- Acceptance check
- Verify the documented command in an agreed environment.
EXAMPLE 02 / CONFLICTING RULESILLUSTRATIVE
Two documents. Two different ways to build.
Suppose the architecture guide requires a shared API client, while agent instructions say to make direct requests. The agent receives conflicting guidance.
Example mismatch / fictional instructions
Architecture guide: use the shared client
Agent instructions: call fetch directly- Suggested change
- Confirm the intended rule with the owner and align both documents.
- Acceptance check
- Check applicable instructions and examples for consistency.
EXAMPLE 03 / UNTESTED BEHAVIORILLUSTRATIVE
A written rule is not proof it gets followed.
Suppose the instructions link to a guide, but there are no task results showing whether the chosen agent follows it. That is a question to test, not a proven failure.
Example validation question
Does the agent follow the linked guide
in the team's agreed workflow?- Suggested next step
- Separately scope repeatable task tests with one agent setup.
- Acceptance check
- Record task outcomes, failures, and what the evidence can establish.
03 / WHAT YOUR TEAM GETS
Know what to fix.
Know where to start.
An AI Repository Context Audit reviews the instructions and documentation your coding agents rely on. Your team gets a clear plan for the problems we can verify.
What your agents are told
A map of the instruction files and project documentation, including gaps and conflicting guidance.
INVENTORYWhat is wrong, and why
Findings tied to actual files, with a clear explanation of the risk and what still needs testing.
AUDIT REPORTWhat to fix first
A prioritized list of recommended changes and a practical way to check each fix.
ACTION PLANA walkthrough with your team
Review the findings together, answer technical questions, and decide who should tackle the next steps.
REVIEW SESSIONAlready using tools like these?
GitHub CopilotClaude CodeCodex
We agree one agent setup to review.
No new platform to adopt.
04 / THE ENGAGEMENT
Small scope.
Clear next steps.
- 01 / TELL US WHAT REPEATS
Start with the mistakes.
Show us where your team keeps correcting the agent. We agree the codebase, agent setup, access, and up to three workflows before work begins.
- 02 / REVIEW THE INSTRUCTIONS
Find what does not match.
We compare your instructions and documentation with an agreed version of the code. Each finding must have supporting evidence.
- 03 / PRIORITIZE THE FIXES
Leave with a plan.
Get the report, recommended changes, and checks your engineers can use. We walk through the priorities with your team.
05 / START WITH ONE CODEBASE
Turn repeat
corrections
into a fix plan.
For CTOs, engineering managers, and technical leads whose teams already use coding agents and keep correcting the same repository-specific mistakes.
You are buying a focused diagnosis and an engineering-ready plan. Your team keeps control of the code and the implementation.
Read the sample before you decideAI REPOSITORY CONTEXT AUDIT
$2,500USD / one time
Proposed pilot price. Due in full after written scope acceptance and before audit work begins.
- Codebase
- 1 agreed repository version
- Coding agent
- 1 setup, up to 3 workflows
- Target turnaround
- 5 business days after access
- Your involvement
- 30-min intake + 45-min review
- Deliverables
- Instruction map, findings, fix plan, review
hello@repochicken.comNo booking or payment on this site.
Clear deliverables. A clear guarantee.
If a core deliverable remains materially incomplete against the written acceptance criteria, tell us within 7 calendar days of delivery. We have 5 business days to correct it. If we cannot, we refund your $2,500 audit fee.
This is an objective deliverables guarantee, not a satisfaction or performance promise. A full refund ends permission to use or distribute the refunded audit.
Read the guarantee and engagement termsAudit and recommendations only. Implementation, security review, and before/after agent trials are separate. Scope, access, and terms must be agreed in writing with MyBFchef LLC before payment.
06 / BEFORE WE BEGIN
Good questions.
Straight answers.
A focused service, with explicit boundaries.
What is an AI repository context audit?
It is a review of the instructions and documentation your coding agents rely on. We check them against your actual codebase for outdated commands, conflicting rules, and missing project knowledge. You get an explanation of each problem, the evidence behind it, and a prioritized fix plan. See the audit checklist.
Why not have an agent generate AGENTS.md?
A new instruction file can still repeat outdated commands, contradict another document, or miss a project rule. We check the instructions against the code and show where changes are justified. The value is the diagnosis and fix plan, not the number of documents produced.
What access do you need?
A read-only copy of the agreed codebase, the relevant coding-agent settings, and examples of mistakes your team keeps correcting. Before receiving private code, we agree which tools may process it, what should be removed, and how long it may be kept. Do not send private code or credentials in your first inquiry.
Will this make our agents faster or cheaper?
The goal is less avoidable rework. The audit gives your team documented findings and recommended next steps; it does not guarantee time savings, lower costs, or better AI performance. Measuring those improvements requires separate task testing in your environment. If we find no actionable problems, we say so.
What does the refund guarantee cover?
A core deliverable that remains materially incomplete against the written acceptance criteria after our 5-business-day correction period. Tell us within 7 calendar days after delivery and identify the specific deficiency. A full refund ends permission to use or distribute the refunded audit. This is not a satisfaction or performance guarantee. Read the full terms.
Do you implement the fixes?
Your team receives the findings, recommended changes, checks for each fix, and a review session. Implementation is not included in the audit fee. Hands-on changes or tests of agent performance would need a separate agreement.
Do we need a new platform or subscription?
No. Recommendations fit your existing repository, documentation, and tools. No new documentation format or platform is required. This is a standalone audit, not a software subscription.
Is the sample a customer case study?
No. It is an illustrative example of the deliverables, not a completed audit or proof of results. The scenarios and snippets are fictional. They show the report format; your audit would use evidence from your agreed repository.
START WITH THE MISTAKE THAT KEEPS COMING BACK