decision-log

decision-log is a skill for Claude Code from kimsanguine/hplan. It costs 88 tokens per session (1,243 once invoked), scanned A, original, MIT.

An append-only record of product decisions such as build, hold, interview, or pivot. It can later compare those decisions with real outcomes over three to six months.

In plain words
What is it for?
Use it to record gate decisions, add later outcomes such as shipped or pivoted, and review measures such as hit rate, false holds, and missed builds.
Why use it?
It preserves the reasons and scores behind decisions, so teams can measure which decisions were accurate instead of relying on memory. Incorrect entries are corrected by adding a new record rather than deleting history.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 hplan/scripts/decision_log.py log \.

Part of the hplan plugin — 8 skills, 11 commands, 4 agents shipped together

Good fit Use it to record gate decisions, add later outcomes such as shipped or pivoted, and review measures such as hit rate, false holds, and missed builds.

Compare 6 skills from other repositories ↓
Install

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.

Clone the repo
git clone --depth 1 https://github.com/kimsanguine/hplan
agentmods
npx agentmods add skills/kimsanguine/hplan/decision-log

Made for: Claude Code.

Or install hplan, the plugin that ships this one along with the rest of its 8 skills, 11 commands, 4 agents.

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 decision-log

README.md
[![agentmods](https://agentmods.dev/badge/skills/kimsanguine/hplan/decision-log.svg)](https://agentmods.dev/skills/kimsanguine/hplan/decision-log)
Your own site
<a href="https://agentmods.dev/skills/kimsanguine/hplan/decision-log"><img src="https://agentmods.dev/badge/skills/kimsanguine/hplan/decision-log.svg" alt="Measured on agentmods" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,243 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 $0.00088 $0.01243
Opus 5 $0.00044 $0.00622
Sonnet 5 $0.00018 $0.00249
Haiku 4.5 $0.00009 $0.00124

Measured 7d ago against content hash e468327b474e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

decision-log 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 7d 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.

hplan/skills/decision-log/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Decision Log — Self-Calibrating Build Gate

Running for: $ARGUMENTS

Core Goal

  • 모든 gate 결정을 harness/decisions.jsonl에 append-only로 기록 → 3-6개월 뒤 audit으로 hit_rate 측정.
  • false_hold (hold 했는데 외부에서 성공함) + missed_build (build 했는데 죽음)을 자동 추출 → rubric 보정 데이터.
  • "내 게이트가 정확한가?"라는 질문에 답할 수 있는 유일한 PM skill.

Trigger Gate

Use This Skill When

  • 매 build/interview/pivot/hold/CONDITIONAL_GO 결정 시 즉시 호출 (의무)
  • 3-6개월 뒤 outcome이 확정됐을 때 backfill
  • 분기별 self-review — "지난 분기 결정 중 정확했던 비율은?"

Route to Other Skills When

  • audit 결과 false_hold 다수 → evidence-rubric의 threshold 검토
  • missed_build 다수 → Evidence Gate 통과 기준 강화
  • decision = hold + 영구 사유 → exclusions add 같이 호출
  • decision = buildhandoff 로 라우팅

Boundary Checks

  • ❌ 영구 삭제 불가 (append-only). 잘못된 entry는 새 entry로 supersede.
  • ❌ outcome backfill 없으면 audit이 의미 없음 — 잊지 말 것.
  • --from-hitl은 이미 기록된 HITL id만 허용. 없는 id를 주면 거부된다 (끊어진 승격 링크 방지).
  • ⚠️ --rootharness/ 자체가 아니라 그 부모 디렉터리를 가리킨다.

Inputs

# Log a decision
python3 hplan/scripts/decision_log.py log \
  --project alpha-app --gate build --decision build --score 78 \
  --reason "5/5 강한 신호" --reason "COGS GREEN"

# Promote an earlier HITL decision into a gate decision
python3 hplan/scripts/decision_log.py log \
  --project alpha-app --gate build --decision build --score 78 \
  --from-hitl hitl-2026-07-28-ab12c

# Backfill outcome (3-6 months later)
python3 hplan/scripts/decision_log.py update --id dec-XXX --outcome shipped

# Audit — single project
python3 hplan/scripts/decision_log.py audit

# Audit — aggregate calibration across several projects
python3 hplan/scripts/decision_log.py audit --root ../alpha --root ../beta

Steps

  1. 결정이 내려진 직후 log 호출 (--reason 다중 사용 권장).
  2. project name + gate (evidence/product/build) + decision 명시.
  3. 매주/매월 audit 호출 — pending decisions 확인.
  4. outcome이 확정되면 즉시 update --id <id> --outcome <state>.
  5. 분기별 audit으로 hit_rate trend 점검.

Outputs

  • harness/decisions.jsonl (append-only)
  • audit returns: total, resolved, pending, by_decision, by_decision_outcome, hit_rate, false_holds, missed_builds, guidance

Read the full file on GitHub · 110 lines

Files

What ships with it

4 files 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. 7d ago First seen · 110 lines · 88 tokens per session scan A e468327b474e

Subscribe to this mod's changes

decision-log is a skill published in the GitHub repository kimsanguine/hplan (2 stars, last pushed 22d ago), licensed MIT. It adds 88 tokens to every session and 1,243 once invoked, about $0.0004 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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