skill-improver
- Repo stars 267
- Author updated Live
- Author repo mini-diarium
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @fjrevoredo · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- macOS · Linux · Windows
- Runtime requirements
- Node.js
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: skill-improver
description: | Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task…
category: ai
runtime: Node.js
---
# skill-improver output preview
## PART A: Task fit
- Use case: | Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task (especially one that hit friction), run this skill to catalog what happened, classify the gaps, and apply fixes — either directly for obvious issues, or via a structured plan for larger changes. runs entirely locally; runs on Node.js. Works with Claude Code, C….
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to Run / Workflow / Step 1 — Reflect” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “| Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task (especially one that hit friction), run this skill to catalog what happened, classify the gaps, and apply fixes — either directly for obvious issues, or via a structured plan for larger changes. runs entirely locally; runs on Node.js. Works with Claude Code, C…”.
- **02** When the source has headings, the agent prioritizes “When to Run / Workflow / Step 1 — Reflect” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “When to Run / Workflow / Step 1 — Reflect”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: skill-improver
description: | Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task…
category: ai
source: fjrevoredo/mini-diarium
---
# skill-improver
## When to use
- | Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task (especially one that…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “When to Run / Workflow / Step 1 — Reflect” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "skill-improver" {
input -> user goal + target files + boundaries + acceptance criteria
context -> When to Run / Workflow / Step 1 — Reflect
rules -> SKILL.md triggers / order / output contract
runtime -> Node.js | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Skill Improver
Turn every hard-earned lesson into a reusable improvement. After completing a non-trivial task (especially one that hit friction), run this skill to catalog what happened, classify the gaps, and apply fixes — either directly for obvious issues, or via a structured plan for larger changes.
When to Run
Proactive (run without being asked):
- A build, deploy, or CI job failed and was debugged
- A task took more than 3 rounds of trial-and-error
- A session lasted more than one hour and involved multiple skill uses
- The user explicitly expressed frustration or surprise at a gap
On-demand (run when the user says):
- "Reflect on this session" / "post-mortem" / "what went wrong"
- "Improve the skill" / "update the skill with these learnings"
- "Lessons learned" / "what should we change"
Scope: Reflect on ALL skills used during the session, plus any repo artifacts and process steps involved. If multiple skills were loaded, review each one. If the session didn't use any skill, focus on repo/process improvements only.
Workflow
Step 1 — Reflect
Catalog observations in three buckets, with concrete examples:
What went well:
- Patterns, tools, or decisions that saved time or prevented errors
- Skill instructions that proved particularly useful
- Diagnoses or fixes that were reached quickly
What went wrong:
- Mistakes, dead ends, or incorrect assumptions
- Skill instructions that were missing, wrong, or misleading
- Manual workarounds that had to be invented on the fly
What was missing:
- Scripts, checks, or tooling that would have caught the issue earlier
- Documentation or guardrails that didn't exist
- Process steps that were skipped or not automated
Step 2 — Classify
Group findings into three categories. For each finding, identify the concrete artifact that needs to change (file path, skill section, CI workflow, etc.).
Skill changes — improvements to an existing skill:
- Missing failure entries in a diagnosis table
- Wrong fix instructions
- Undocumented pitfalls or edge cases
- Better log access or debugging workflows
Repo artifact changes — new or modified files in the repository:
- Utility scripts (e.g.,
check-node-sources.mjs) - CI workflow steps or pre-release checks
- Configuration or lockfile validation
Process changes — workflow or convention changes:
- Release checklist items
- Pre-commit or pre-tag validation steps
- Cross-skill integration (e.g., pre-release skill should validate lockfiles)
Step 3 — Apply
If no improvements are identified: state that explicitly and stop. Do not invent changes.
The user can always override the plan/execute decision. If the user says "just fix it directly" for something that would normally need a plan, apply the changes directly instead. If the user says "make a plan" for something small, create one.
For obvious fixes (typos, missing warnings, incomplete instructions): Apply directly to the target file using the Edit tool. These are changes where:
- The fix is a single addition or correction to an existing section
- There's no design decision to make
- The change can't break anything else
- Example: adding a missing failure entry to a diagnosis table, or a warning about a known pitfall
For structural changes (new sections, new scripts, reorganized workflows): Create a plan using the manual-planning skill's format. These are changes where:
- The fix requires creating a new file or reorganizing existing content
- Multiple files are affected
- The user should review the approach before implementation
- Example: adding a new utility script, restructuring a skill's diagnosis workflow, adding pre-release steps
Step 4 — Verify
After applying fixes (directly or via plan execution):
- Run format/lint commands if the changed files are in checked languages
- For scripts, run a syntax check and a quick smoke test
- Re-read the changed skill sections to ensure they don't contradict other parts of the skill or adjacent skills
- Summarize what was changed and why
Output Format
At the end, present using this template:
## Session Reflection
### What Went Well
- [item]
### What Went Wrong
- [item]
### What Was Missing
- [item]
## Changes Made
| File | Change |
|------|--------|
| path/to/file | what changed and why |
<!-- If no changes were made: -->
No improvements identified.
If a plan was created, add: **Plan:** docs/plan-name.md — awaiting approval.
Gotchas
- Don't over-improve. If the session went smoothly and no concrete gaps were found, say so and stop. Inventing minor tweaks dilutes the skill.
- One session, one reflection. Don't chain multiple reflection cycles. If the user wants another, they'll ask.
- Obvious fix ≠ trivial preference. "I'd word this differently" is a preference, not a fix. Only apply direct edits when the current text is objectively wrong or missing.
- Respect the user's override. If the user says "just fix it" for something structural, apply directly. If they say "make a plan" for something small, create one. Their call always wins.
Integration with Other Skills
- Use manual-planning for any change that needs a plan (structural changes)
- Use todo-manager if the reflection surfaces new TODO items for the backlog
- The output format mirrors what you'd see in a good commit message: what, why, and where
Decide Fit First
Design Intent
How To Use It
Boundaries And Review