“That command is out of date.”
Setup and validation instructions survived the migration. Your agent is still following them.
Inspect: stale operational guidanceFOR TEAMS ALREADY BUILDING WITH CODING AGENTS
AI Repository
Context Audit.
- THE ENGAGEMENT
- One repository. A focused review.
- THE HANDOFF
- Evidence. Priorities. A plan to act on.
- THE COMMITMENT
- A standalone audit. No subscription.
Grounded in your actual setup
GitHub Copilot / Claude Code / Codex
One agreed agent environment per audit01 / THE FRICTION
Better tools.
The same corrections.
Your engineers should not have to explain the same repository rules every time they delegate a task.
“We don't build it that way.”
The architecture decision exists. The path from the agent's instructions to that decision does not.
Inspect: missing context routes“I already explained this.”
Useful knowledge is buried in chat history, repeated across files, or contradicted by another instruction.
Inspect: gaps and conflicting rulesContext is one possible cause. The audit separates supported findings from issues that need a live workflow test.
02 / SEE THE WORK
A finding you can
actually act on.
This is an audit of our own repository. Every finding points to inspected evidence, explains its consequence, and proposes a checkable correction.
First-party demonstration. No customer results or productivity claims.
03 / WHAT YOU RECEIVE
From “something is off”
to a prioritized next step.
A repository context audit compares agent instructions and supporting knowledge with the codebase they describe. You receive a practical handoff for the engineers who will make the changes.
A map of the context
Entry points, instruction scope, knowledge routes, and where the selected agent's behavior still needs verification.
INVENTORYFindings with evidence
File-level references, conflicting or stale guidance, likely consequences, and confidence in each conclusion.
AUDIT REPORTA sequenced fix list
What to keep, change, move, or remove. Each recommendation includes priority and an acceptance check.
REMEDIATION PLANA technical handoff
Walk through the findings together, resolve questions, and agree which hypotheses to validate next.
REVIEW SESSIONThe audit identifies and recommends changes. Implementation and controlled before/after agent runs are separately scoped. Read the repository context guide.
04 / HOW IT WORKS
Small scope.
Clear handoff.
- 01 / SCOPE
Start with the friction.
Choose a repository, an agent environment, and up to three workflows your team wants to improve.
- 02 / INSPECT
Follow the evidence.
Review a fixed snapshot. Trace instructions to code, commands, and the knowledge they reference.
- 03 / DELIVER
Know what to change.
Receive the findings and prioritized plan, with acceptance checks your engineers can use.
- 04 / REVIEW
Leave with a next step.
Discuss the findings and decide whether your team or a separate implementation engagement takes them forward.
05 / FOUNDING CUSTOMER AUDIT
Start with
one repository.
A focused first engagement for engineering leaders who want a concrete plan before investing in a broader rollout.
A good fit: an active codebase, an existing coding-agent workflow, and an engineer available to explain the recurring friction.
Not a security audit, code-quality review, or guarantee of agent performance.
PROPOSED PILOT PACKAGE
$2,500USD / one-time
Illustrative offer for this local prototype. Price and delivery timing are not validated commitments.
- Scope
- 1 repository · 1 agent setup
- Workflow review
- Up to 3 agreed workflows
- Proposed turnaround
- 5 business days after access
- Your involvement
- 30-min intake + 45-min review
- You receive
- Report + prioritized fix list
Contact: michael@mybfchef.com. No booking or payment is taken.
First step: share your setup and recurring friction. Scope and access would be agreed before work begins.
06 / BEFORE YOU START
Good questions.
Direct answers.
Why not just ask our coding agent to write AGENTS.md?
Generating instructions is one step. The audit checks whether those instructions match your repository, conflict with other guidance, and lead to usable workflow knowledge. The handoff includes evidence and acceptance checks so your team can judge the recommendations.
What access would you need?
A read-only repository snapshot, the relevant agent configuration, and examples of the friction you see. An exported or redacted snapshot can be discussed; missing material limits what we can conclude. Running commands or agent trials requires a separately agreed environment.
How would private code be handled?
Before a real engagement, we would agree access, permitted tools and model providers, retention, and deletion in writing. This local prototype does not accept repository uploads. Our demonstration uses only our own repository.
Will the audit make our agents faster or cheaper?
It can identify unnecessary context and actionable instruction problems. A reduction in file size is not proof of faster work, lower billed tokens, or better task completion. Those outcomes need repeated, controlled runs in your actual environment.
Are the fixes included?
The proposed audit includes findings, recommendations, acceptance checks, and a handoff session. Your team can implement the plan. Any implementation work or before/after agent evaluation would be agreed separately.
Do we need OKF or a new platform?
No. Recommendations should fit your repository and tools. Open Knowledge Format can help organize knowledge for selective reading, but adopting it is not a condition of the audit. There is no platform subscription.
Does founding pricing require a case study?
No. Any future use of anonymized findings would require explicit permission. A case study is optional and separate from the audit.
GIVE YOUR TEAM A CLEARER STARTING POINT.