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 avizmarlon/agent-skills --skill ledger-auto-updatesgit clone --depth 1 https://github.com/avizmarlon/agent-skillsWrote 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/avizmarlon/agent-skills/ledger-auto-updates)<a href="https://agentmods.dev/skills/avizmarlon/agent-skills/ledger-auto-updates"><img src="https://agentmods.dev/badge/skills/avizmarlon/agent-skills/ledger-auto-updates/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/avizmarlon/agent-skills/ledger-auto-updates"><img src="https://agentmods.dev/badge/skills/avizmarlon/agent-skills/ledger-auto-updates.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 | $0.00052 | $0.02158 |
| Opus 5 | $0.00026 | $0.01079 |
| Sonnet 5 | $0.00010 | $0.00432 |
| Haiku 4.5 | $0.00005 | $0.00216 |
Grade A, and why
ledger-auto-updates 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 12d 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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ledger Auto-Updates — Automatic Session Closure with Living Documentation
Ledger updates (CHANGELOG + session-handoff or project equivalents) are part of session closure — not a manual decision tree, and not something the user should have to request. If the user had to ask "should we update the ledger?", the agent failed.
Principle
The agent detects session-end conditions and automatically updates the project's living documentation to reflect:
- What changed during this session (CHANGELOG entry)
- State for the next agent picking up the work (session-handoff entry)
This ensures continuity across multiple AI-agent sessions without explicit handoff ceremony each time.
Triggers — Update without asking when you detect:
- Farewell signals: natural language indicating the session is ending (e.g., "thanks, see you later", "that's all for now", "wrapping up", "good night")
- Explicit wrap-up request: user says "close the session", "prepare for next phase", "create handoff", "open new session"
- Clear topic pivot: moving to an unrelated topic after completing a coherent block of work (e.g., finished a bugfix phase, now asking about a different project)
- User explicitly asks about the ledger: "Should we update CHANGELOG/handoff?" or similar. If they're asking, you missed the trigger. Update immediately and acknowledge the miss.
- Session running long: approaching context limit (>50% full) with substantive work completed
- Before declaring work complete: any message framing closure ("all set", "ready for next session", "finished") must be preceded by ledger updates
Criterion: What counts as "substantive work"
Update the ledger if ANY of these happened:
- Code merged into main branch (commit, PR, or direct push)
- Non-trivial architectural or product decision made
- Bug root cause identified and fixed, with a reusable lesson for other teams
- Changes to rules, instructions, or multi-tool agent configuration
- Significant debugging session that produced a new finding or pattern
- Repository state changed meaningfully (deleted worktrees, removed stale branches, refactoring)
- New tool, wrapper, script, or reusable helper created
- Configuration, MCP setup, or credentials changed in a way that affects workflow
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.
- 12d ago First seen · 221 lines · 52 tokens per session scan A c719c91f7a71
ledger-auto-updates is a skill published in the GitHub repository avizmarlon/agent-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 52 tokens to every session and 2,158 once invoked, about $0.0003 per session on Opus 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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