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 agentmods add commands/xiaolai/echo-sleuth-for-claude/auditgit clone --depth 1 https://github.com/xiaolai/echo-sleuth-for-claudeWrote 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/commands/xiaolai/echo-sleuth-for-claude/audit)<a href="https://agentmods.dev/commands/xiaolai/echo-sleuth-for-claude/audit"><img src="https://agentmods.dev/badge/commands/xiaolai/echo-sleuth-for-claude/audit.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00289 |
| Opus 5 | $0.00000 | $0.00144 |
| Sonnet 5 | $0.00000 | $0.00058 |
| Haiku 4.5 | $0.00000 | $0.00029 |
Grade A, and why
audit 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 5d 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.
What it actually says
Audit Claude Code memories for staleness.
Arguments: $ARGUMENTS
Parse arguments:
- If
--deepis present: dispatch thememory-auditoragent for content-aware verification - If a project name/path is given: filter to that project
- Otherwise: audit all projects with memories
Without --deep (default):
Run the heuristic audit script:
bash "${CLAUDE_PLUGIN_ROOT}/scripts/memory-dashboard.sh" --project PROJECT_IF_SPECIFIED
Present the detailed staleness table. For each memory with score > 50, show:
- File path
- Type and age
- Score and recommended action
Suggest /prune for memories recommended for pruning, or /audit --deep for content verification.
With --deep:
Launch the memory-auditor agent via the Task tool with:
- Target project: from arguments (or "all" if not specified)
- Memory files: list all memory files to audit (from dashboard script output)
- Project roots: resolved project root paths for file/code verification
The memory-auditor agent will verify claims in memory content against current project state and produce a detailed report.
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.
- 5d ago First seen · 38 lines · 0 tokens per session scan A 09ec56f0d44b
audit is a command published in the GitHub repository xiaolai/echo-sleuth-for-claude (9 stars, last pushed 12d ago), licensed ISC. It costs nothing until one of its globs matches a file; then it loads 289 tokens. 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.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.