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Agent skill

Record Spec Feedback

by haru in haru/redmine_ai_helper

Record a user's correction of an AI-written specification in docs/spec-feedback/ as an append-only entry with root-cause analysis.

MITAuto-check passedDevelopment

Install Record Spec Feedback

skills CLI
$ npx skills add haru/redmine_ai_helper --skill record-spec-feedback -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install haru/redmine_ai_helper record-spec-feedback --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/haru/redmine_ai_helper.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/record-spec-feedback .claude/skills/record-spec-feedback && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
record-spec-feedback
GitHub stars
106
Token cost
~1k tokens
SKILL.md length
558 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

Record a user's correction of an AI-written specification in docs/spec-feedback/ as an append-only entry with root-cause analysis.

  • Works in 8 steps: Read the Rules → Collect the Feedback → Check Existing Entries → …
  • Asks to log spec feedback
  • SKILL.md covers User Input, Procedure and Notes
  • Calls git

What it does

Record Spec Feedback is an agent skill from haru/redmine_ai_helper. Record a user's correction of an AI-written specification in docs/spec-feedback/ as an append-only entry with root-cause analysis. Use right after applying a user-requested fix to spec.md, plan.md, tasks.md, or a design document (AGENTS.md and the constitution require this), or when the user asks to log spec feedback. Skips typo-only and wording-only fixes.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Root cause analysis. The repository describes itself as: A Redmine plugin that adds AI agents, MCP Server, smart completion, and vector search. The licence is MIT.

When your agent uses it

  • Asks to log spec feedback
  • Tasks that involve Root cause analysis

Example prompts

  • “/record-spec-feedback”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Read the Rules
  2. Collect the Feedback
  3. Check Existing Entries
  4. Analyze the Root Cause
  5. Write the Prevention Rule
  6. Create the Entry
  7. Propose Promotion When It Recurs
  8. Report

What it can do on your machine

Read from SKILL.md and the folder at commit 54cee42. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Record Spec Feedback loads about 1k tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 558 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from haru/redmine_ai_helper at commit 54cee42, republished under its MIT licence (© haru). 558 words, ~1,042 tokens.

Download SKILL.mdSave it as .claude/skills/record-spec-feedback/SKILL.md (or your agent's skills folder).
name
record-spec-feedback
description
Record a user's correction of an AI-written specification in docs/spec-feedback/ as an append-only entry with root-cause analysis. Use right after applying a user-requested fix to spec.md, plan.md, tasks.md, or a design document (AGENTS.md and the constitution require this), or when the user asks to log spec feedback. Skips typo-only and wording-only fixes.
argument-hint
Optional: the feedback to record, the feature/artifact, or extra context about why the original was wrong
user-invocable
true
disable-model-invocation
false

Record Spec Feedback

Record a correction the user requested on an AI-written specification, analyze why the AI wrote it that way, and derive a rule that prevents the same mistake next time.

User Input

text
$ARGUMENTS

Consider any context from the user input (which feedback to record, which feature, the user's own view of the cause) before proceeding.

Procedure

Step 1: Read the Rules

Read docs/spec-feedback/README.md. It defines what to record, the root-cause categories, the template, and the index. Follow it; this skill only describes the workflow.

Step 2: Collect the Feedback

From the conversation and the working tree, identify:

  • The user's correction request (their words, translated faithfully into English if needed)
  • The affected feature (specs/NNN-... directory or branch) and artifact file
  • The original AI-written text and the corrected text — use git diff on the artifact, or the conversation history when the file is not tracked (specs/ is gitignored)

Record only corrections that have been applied. If the fix is not applied yet, apply it first.

Stop without recording if every point is a typo fix or a wording change that does not change meaning, and tell the user why.

If the request contains several points, group them by root cause: one entry per root cause.

Step 3: Check Existing Entries

Scan the index in the README and open entries with the same category or a similar topic. If an existing entry describes the same pattern, list it under Related.

Step 4: Analyze the Root Cause

Answer concretely:

  • What did the AI base the original text on (request wording, an existing spec, the code, a guess)?
  • What should it have read or asked instead — name the file, wiki page, ADR, or question?
  • Why did it not do so (information absent, ambiguity not noticed, convention not documented, over-generalization)?

Pick the category from the README table. Use other only with an explanation.

Show full SKILL.md (250 more words)Show less
Step 5: Write the Prevention Rule

Write a rule that is concrete and checkable at spec-writing time (e.g. "When a spec introduces a new setting, state its default; ask the user if the request does not give one" — not "be more careful"). Set Promoted to to Not yet unless the rule is actually added to a durable place.

Step 6: Create the Entry
  1. Find the highest existing number in docs/spec-feedback/ and add one (start at 001).
  2. Create docs/spec-feedback/NNN-short-title.md from the template, in English, with today's date.
  3. Append a row to the README index: | [SF-NNN](./NNN-short-title.md) | Title | category | feature | Not yet |.

Never edit or delete existing entries, except for updating the Promoted to field in Step 7.

Step 7: Propose Promotion When It Recurs

If the new entry has one or more Related entries (the pattern has occurred at least twice), propose to the user where the prevention rule should be promoted (AGENTS.md, the constitution, a skill) and show the proposed text. Do not change those files without the user's approval. After the approved rule is added, update the entry's Promoted to field and the matching index cell to name the destination.

Step 8: Report

Tell the user the created file, the category, the prevention rule, and any promotion proposal. Do not commit.

Notes

  • Write entries in English regardless of the conversation language.
  • Keep excerpts short, but make each entry self-contained: specs/ is gitignored, so quote the lines needed to understand the correction instead of linking to the artifact.

© haru, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/record-spec-feedback of haru/redmine_ai_helper.

Open the folder on GitHubat commit 54cee42

Compare with similar skills

Record Spec Feedback next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Record Spec Feedback compared with similar skills
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Record Spec Feedback this skillharu/redmine_ai_helper106—~1kAutomated safety check: PassMIT
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Muse Code Product Doctorasgeirtj/system_prompts_leaks69k—~3.5kAutomated safety check: PassCC0-1.0
PRP Implementation PlannerWirasm/prp2.3k—~4.1kAutomated safety check: PassMIT
PRP PlanWirasm/prp2.3k—~4kAutomated safety check: PassMIT
Optimize Protocol0x0funky/vibehq-hub195—~3.2kAutomated safety check: PassMIT

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Categories

Questions about Record Spec Feedback

What does Record Spec Feedback do?

Record a user's correction of an AI-written specification in docs/spec-feedback/ as an append-only entry with root-cause analysis. Record Spec Feedback is an agent skill from haru/redmine_ai_helper. Record a user's correction of an AI-written specification in docs/spec-feedback/ as an append-only entry with root-cause analysis.

When should I use Record Spec Feedback?

Record Spec Feedback fits situations like: asks to log spec feedback; tasks that involve Root cause analysis.

How do I install Record Spec Feedback in Claude Code?

Run `npx skills add haru/redmine_ai_helper --skill record-spec-feedback -a claude-code`. Or copy the skill folder (.claude/skills/record-spec-feedback in haru/redmine_ai_helper) into .claude/skills/record-spec-feedback in your project. Claude Code loads it when a task matches its description.

How do I install Record Spec Feedback in Codex?

Run `npx skills add haru/redmine_ai_helper --skill record-spec-feedback -a codex`. Or copy the skill folder (.claude/skills/record-spec-feedback in haru/redmine_ai_helper) into .agents/skills/record-spec-feedback in your project. Codex loads it when a task matches its description.

Can I use Record Spec Feedback in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add haru/redmine_ai_helper --skill record-spec-feedback -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/record-spec-feedback, .gemini/skills/record-spec-feedback, .github/skills/record-spec-feedback and .opencode/skills/record-spec-feedback in your project.

What does Record Spec Feedback need to run?

Going by SKILL.md and its folder, Record Spec Feedback needs the command-line tools its instructions call (git).

Does Record Spec Feedback access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Record Spec Feedback safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Record Spec Feedback use?

Record Spec Feedback is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Record Spec Feedback use?

About 1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Record Spec Feedback?

Skills that share tags, products or a category with Record Spec Feedback: Octocode Code Research (bgauryy/octocode, 949 stars), Muse Code Product Doctor (asgeirtj/system_prompts_leaks, 69k stars), PRP Implementation Planner (Wirasm/prp, 2.3k stars) and PRP Plan (Wirasm/prp, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Record Spec Feedback?

haru (a GitHub user) maintains it in haru/redmine_ai_helper, which has 106 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on October 11, 2026.

Source: haru/redmine_ai_helper on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.