decisions-logger

decisions-logger is a skill for Claude Code from vidhunnan/agentic-skills. It costs 135 tokens per session (7,390 once invoked), scanned A, original, MIT.

A decision record generator that finds choices already made in a code project and documents them with evidence. An ADR is a dated note explaining an important technical decision and its reasons.

In plain words
What is it for?
Use it to create numbered decision records, organize them in an index, track replaced decisions, and record follow-up questions.
Why use it?
It makes the history behind project choices easier to find while reducing the risk of inventing reasons that were never recorded.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions CLAUDE.md; names the AskUserQuestion tool; mentions Claude Code.

Part of the decisions-logger plugin — 1 skill shipped together

Good fit Use it to create numbered decision records, organize them in an index, track replaced decisions, and record follow-up questions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vidhunnan/agentic-skills/decisions-logger
Install

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.

Any agent
npx skills add vidhunnan/agentic-skills --skill decisions-logger
Clone the repo
git clone --depth 1 https://github.com/vidhunnan/agentic-skills

Made for: Claude Code.

Or install decisions-logger, the plugin that ships this one along with the rest of its 1 skill.

Wrote 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.

agentmods badge for decisions-logger

README.md
[![agentmods](https://agentmods.dev/badge/skills/vidhunnan/agentic-skills/decisions-logger/github.svg)](https://agentmods.dev/skills/vidhunnan/agentic-skills/decisions-logger)
Your own site
<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.

agentmods 80×15 button for decisions-logger

Your own site · 80×15
<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>
Per session 135 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,390 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 11d ago against content hash fa95234c1178, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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.

skills/decisions-logger/SKILL.md · 356 lines

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).

Read the full file on GitHub · 356 lines

Files

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.

Changes

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.

  1. 11d ago First seen · 356 lines · 135 tokens per session scan A fa95234c1178

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens