Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add murray17/rovai-ai --skill analyze-agent-codebasegit clone --depth 1 https://github.com/murray17/rovai-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/murray17/rovai-ai/analyze-agent-codebase)<a href="https://agentmods.dev/skills/murray17/rovai-ai/analyze-agent-codebase"><img src="https://agentmods.dev/badge/skills/murray17/rovai-ai/analyze-agent-codebase/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/murray17/rovai-ai/analyze-agent-codebase"><img src="https://agentmods.dev/badge/skills/murray17/rovai-ai/analyze-agent-codebase.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.00813 |
| Opus 5.5 | $0.00019 | $0.00325 |
| Sonnet 5.5 | $0.00009 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
analyze-agent-codebase scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 20d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Agent Codebases
Reconstruct behavior from real entry points, call chains, state transitions, and persistence. Documentation explains intent; code and tests establish implementation. Respond in the user's language unless asked otherwise.
Boundaries
- Follow repository instructions, documentation routes, and read-only constraints.
- Default to read-only. Write analysis documents only when requested; do not modify implementation.
- Use source, dependency wiring, configuration, schemas, migrations, and tests as evidence.
- Label important claims
confirmed,inferred, orunknown, localizing these labels in the report. Explain inferences and gaps. - Cite paths, symbols, and relevant entry-to-effect call chains. Names such as agent, memory, plan, or tool do not prove capabilities.
Choose the scope
Use the smallest sufficient scope: a vertical slice for a mechanism question, an architecture report for several mechanisms, or a dossier when multiple documents are requested. For a dossier, read analysis axes and structure.
Check existing analyses for scope, evidence, and revision; update the appropriate document instead of creating duplicate overviews.
Investigate
- Freeze scope. Record repository root, revision, requested questions, exclusions, output format, languages, build entry points, generated directories, and initial worktree state. Distinguish production code from tests, fixtures, examples, generated code, vendors, and historical documents.
- Trace the runtime. Follow entry point -> configuration and dependency wiring -> agent/workflow construction -> execution loop -> model, tool, collaboration, and persistence effects -> events, recovery, and presentation. Follow registries through loaders, macros, decorators, or configuration until the actual implementation is connected.
- Trace each question vertically. Use a real trigger: input -> authorization and validation -> state change -> effects -> result -> error and recovery. Select only mechanisms present in the code.
- Record evidence as you read. Use the table below. A claim about subagents, for example, needs the creator, context transfer, isolation, and result path.
- Explain ownership. Identify control and state authority, sync/async connections, context/session/Memory/history lifecycles, tool/Skill/prompt/permission boundaries, and failure, retry, cancellation, idempotency, and recovery limits. Record documentation drift.
- Cross-check. Reverse-reference key symbols to verify production wiring. Inspect tests, schemas, flags, platforms, adapters, and alternate entries. Tests prove only covered behavior; mark unexecuted checks
not_run. Compare authoritative documentation unless the user prohibits reading it.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 20d ago Changed · -82 lines · -52 tokens per session 7ae81b15888b
- 1mo ago First seen · 126 lines · 99 tokens per session scan A f4eb72dee133
analyze-agent-codebase is a skill published in the GitHub repository murray17/rovai-ai (201 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 813 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
Read-only review
Review the selected implementation and report correctness, security, and maintainability findings. Do not modify workspace files.
debug-test-failure
Systematically diagnose a failing test instead of guessing at fixes.
write-runbook
Turn an incident response into a reusable runbook the next on-call can follow.
api-design-review
Review a new or changed API surface against the contract concerns that bite later.
investigate-performance-regression
Narrow down what made something slower using measurement, not intuition.
onboard-new-engineer
Structure a new engineer's first week so they ship and build context, not just read.