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 vidhunnan/agentic-skills --skill decisions-loggergit clone --depth 1 https://github.com/vidhunnan/agentic-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/vidhunnan/agentic-skills/decisions-logger)<a href="https://agentmods.dev/skills/vidhunnan/agentic-skills/decisions-logger"><img src="https://agentmods.dev/badge/skills/vidhunnan/agentic-skills/decisions-logger/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/vidhunnan/agentic-skills/decisions-logger"><img src="https://agentmods.dev/badge/skills/vidhunnan/agentic-skills/decisions-logger.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 | $0.00135 | $0.07390 |
| Opus 5 | $0.00068 | $0.03695 |
| Sonnet 5 | $0.00027 | $0.01478 |
| Haiku 4.5 | $0.00014 | $0.00739 |
Grade A, and why
decisions-logger 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 — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.
decisions-logger
Fills the decisions tier — the folder that answers "why did we choose that?". It mines a project for choices that were really made, and writes each as a numbered ADR with the evidence it came from.
Decisions are the truth tier: past tense, append-only, superseded rather than edited. Which makes this skill's one real risk the whole design problem: mining a repo for "why we chose X" is exactly where a model invents rationale that sounds right. A plausible fabricated reason is indistinguishable from a real one to every future reader, and it poisons the tier the rest of the project trusts.
So the guiding rule, inherited from changelog-tracker, is faithful, not generative: every clause traces to a source or to the user's own words.
Two principles do the work:
- A candidate may be born in a weak source. It may never be justified by one. Some files state a rule and never state its reason (
branch names carry no area segment). You must be able to find those decisions — so you read the file — but their prose can never reach an ADR's reasoning fields. It is a firewall, not a ban. - "I don't remember" is always an option. Every interview question offers it, and it produces a real ADR with the reason recorded as
*(reason not stated)*. A decision with an honest gap is worth more than one with a plausible fiction.
Instructions
Step 0 — Detect your surface
Decide where you're running, using Bash availability:
- Claude Code — Bash works, real filesystem and git. Full flow.
- Claude.ai — no filesystem, no git, no existing ADRs to compare against. Degrade: ask the user to paste their decisions index (or say there isn't one), run the interview conversationally, and emit each ADR as a downloadable artifact plus the index region and the CLAUDE.md block to paste. Say plainly that dedup, supersession detection, and the shipping cross-check are unavailable here — do not guess at them.
Confirm the repo: git rev-parse --show-toplevel. If it fails, the git-anchored sources are gone; say so and degrade (see Step 15).
What ships with it
1 file 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.
- 11d ago First seen · 356 lines · 135 tokens per session scan A fa95234c1178
decisions-logger is a skill published in the GitHub repository vidhunnan/agentic-skills (2 stars, last pushed 5d ago), licensed MIT. It adds 135 tokens to every session and 7,390 once invoked, about $0.0007 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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