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 cpliakas/claude-code-engineering-leaders --skill audit-agent-memorygit clone --depth 1 https://github.com/cpliakas/claude-code-engineering-leadersWrote 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/cpliakas/claude-code-engineering-leaders/audit-agent-memory)<a href="https://agentmods.dev/skills/cpliakas/claude-code-engineering-leaders/audit-agent-memory"><img src="https://agentmods.dev/badge/skills/cpliakas/claude-code-engineering-leaders/audit-agent-memory/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/cpliakas/claude-code-engineering-leaders/audit-agent-memory"><img src="https://agentmods.dev/badge/skills/cpliakas/claude-code-engineering-leaders/audit-agent-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00081 | $0.02349 |
| Opus 5.5 | $0.00032 | $0.00940 |
| Sonnet 5.5 | $0.00016 | $0.00470 |
| Haiku 4.5 | $0.00008 | $0.00235 |
Grade A, and why
audit-agent-memory 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 1mo 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 — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Agent Memory
Audit one agent's project memory directory for four categories of hygiene issues. Produces a structured advisory report with recommended actions. Does not modify any files.
If invoked without an argument, report:
Usage: /audit-agent-memory <agent-name>
Example: /audit-agent-memory qa-lead
Provide the agent name (e.g. qa-lead, tech-lead, product-owner) to audit
that agent's project memory directory.
And exit without reading any file.
Process
1. Read Memory
Derive the memory directory path from the argument:
.claude/agent-memory/engineering-leaders-<agent-name>/
Attempt to read .claude/agent-memory/engineering-leaders-<agent-name>/MEMORY.md.
If the directory or MEMORY.md does not exist, report:
No memory directory found at .claude/agent-memory/engineering-leaders-<agent-name>/.
Run /onboard or /onboard-<agent-name> to create one.
And exit.
Glob the directory for all *.md files:
.claude/agent-memory/engineering-leaders-<agent-name>/*.md
Read every *.md file found. Collect:
- The content of
MEMORY.md(used for dead-link detection) - The content and byte size of every
*.mdfile (used for Check 4 (size)) - A list of all
*.mdfile paths found (used for dead-link detection)
2. Run Checks
Run the four checks below against the collected files. Each check records findings independently. A single file can produce findings under multiple checks.
Check 1: State-Like Content
Heuristic: A file contains state-like content if it matches any of the following patterns:
Dated phrases (any of these strings, case-insensitive):
as oflast quarterlast monthlast sprintthis quarterthis monththis sprintcurrent sprintcurrent phasein progressblocked byQ1,Q2,Q3,Q4followed by a four-digit year (e.g.Q3 2025)
Enumerated file paths: Three or more lines in the file that match the
pattern path/to/file (a sequence of path segments separated by /, not
starting with http). Count consecutive or near-consecutive path-formatted
lines; if three or more appear in the file, this heuristic triggers.
Threshold: 3 or more enumerated paths.
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.
- 1mo ago First seen · 271 lines · 81 tokens per session scan A 364234583986
audit-agent-memory is a skill published in the GitHub repository cpliakas/claude-code-engineering-leaders (4 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 2,349 once invoked, about $0.0003 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 2026-08-31.
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