Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wrg32786/aigent-osnpx agentmods add skills/wrg32786/aigent-os/nightly-ledger-captureWrote 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/wrg32786/aigent-os/nightly-ledger-capture)<a href="https://agentmods.dev/skills/wrg32786/aigent-os/nightly-ledger-capture"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/nightly-ledger-capture/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/wrg32786/aigent-os/nightly-ledger-capture"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/nightly-ledger-capture.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 | $0.00040 | $0.01085 |
| Opus 5 | $0.00020 | $0.00543 |
| Sonnet 5 | $0.00008 | $0.00217 |
| Haiku 4.5 | $0.00004 | $0.00109 |
Grade A, and why
nightly-ledger-capture 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 11d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/nightly-ledger-capture
This is Leg F's capture protocol. It keeps human judgment human-gated while making mechanical claims reproducible.
Local sources
Read:
- today's valid capsules by frontmatter
created_at; - canonical dated Session Log blocks;
- explicitly referenced local Git commits and diffs;
- current
HONESTY_LEDGER.md,TRUST_DECAY.md, andFAILURE_MODES.md; DECISION_LOG.mdandDECISION_OUTCOMES.md.
These sources discover claims. An agent-authored capsule or log entry cannot verify its own claim. The implementation has no dependency on an external coordination service and reports its source scope as local memory plus Git.
Candidate predicates
Honesty
Stage when the day contains consequential multi-file work, a large change, a verified/shipped/deployed/merged claim tied to an artifact, or an uncaptured tradeoff/cost/stopped-short statement. Honesty classification requires judgment, so it is always staged.
Trust decay
Stage the one to three most consequential confident claims only when consequential work is also present. Capture the exact claim, claimant, source reference, and proposed executable resolution predicate. Later narration is not a resolution oracle.
Failure mode
Stage when a diagnosis contains a verified cause plus a real red-before and green-after receipt and the class is not already represented.
Decision outcome
An exact operator answer has already crossed its human gate. Direct append is legal only when all are true:
- exact authored text is
HELD | DRIFTED | REVERSED | STILL UNCLEAR; - decision date and exact heading uniquely match one decision;
- interval is exactly 30, 60, or 90 days and is due inside the documented tolerance;
- the interval is absent from the matching outcome entry; and
- the pre-write SHA-256 still matches.
Invoke:
node daemons/nightly-decision-outcome.mjs --root <aigent-root> \
--as-of <YYYY-MM-DD> --decision-date <YYYY-MM-DD> \
--decision-title "<exact heading>" --interval <30|60|90> \
--outcome "<enum>" --operator-text "<exact enum>" \
--operator-source "<durable direct operator ref>" \
--expected-file-sha "<pre-read sha256>"
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.
- 11d ago First seen · 141 lines · 40 tokens per session scan A a5106bf17648
nightly-ledger-capture is a skill published in the GitHub repository wrg32786/aigent-os (18 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 1,085 once invoked, about $0.0002 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 2026-09-01.
Other skills, from other repositories
hive.colony-progress-tracker
Claim tasks, record step progress, and verify SOP gates in the colony SQLite queue. Applies when your spawn message includes a dbpath field.
operator-scorecard
Three recap modes - default synthesizes agent health, community growth, and economic activity into a was-it-worth-it verdict; ops recaps what shipped and failed; push ranks push impact.
github-monitor
Watch your GitHub repos across four views - a combined urgency monitor (stale PRs, new issues, releases), a new-issue triage queue, a release upgrade digest, or your own opened-PR tracker.
heartbeat
Ambient fleet-health check that surfaces anything worth attention (default), or an on-demand priority brief - the 3 things to focus on, why now, and what moved (var=brief).
shiplog
Recap of everything shipped since the last run - cross-repo PRs, security fixes, star deltas, and X traction, synthesized into a digest article and a ready-to-post shiplog in your voice.
idea-pipeline
Execution-gap audit - cross-references the startup idea backlog against shipped skills, prototypes, and cross-repo PRs, surfacing the top 3 ideas to build next by narrative and operator fit.