/technical-skill-finder

name: technical-skill-finder
description: Mine coding agent logs (Codex/Cursor/session histories and similar telemetry) to discover high-value candidate skills, then draft structured skill creation/reuse recommendations.
license: MIT
metadata:
  source: "https://github.com/vincentkoc/dotskills"

Technical Skill Finder

Purpose

Find recurring pain points from local agent logs and convert them into actionable skill candidates, reuse opportunities, or existing skill updates.

When to use

• You want to discover missing technical skills from historical agent activity.
• You want reproducible criteria before creating a new skill.
• You want to validate whether an existing skill already covers the pattern.
• You want to include optional personal-signal sources (when authorized).

Inputs

• `SCOPE` (required): repository paths, workspace, or tool domains to inspect.
• `SOURCES` (required): ordered source list to mine.
• `TIMEFRAME` (optional): default `all` unless constrained by user.
• `PRIVACY_POLICY` (required): explicit user direction for personal logs.
• `TOP_N` (optional): number of highest-priority candidates to return.

Workflow

1. Initialize source set

• `~/.codex/history.jsonl`
• `~/.codex/archived_sessions/*.jsonl`
• `~/.codex/sessions/*.jsonl` and `~/.codex/log/*` if present
• Repository-specific telemetry in `AGENTS.md`/local docs when available
• `Cursor` / `Codex` agent logs detected under known dotfiles directories

2. Normalize extraction signals

• Parse stack traces and classify failure type (`auth`, `type-check`, `llm-error`, `git/ci`, `runtime`, `refactor-merge`, `test`)
• Parse recurring command phrases (`rg`, `mypy`, `pytest`, `gh`, `git`, package-manager failures)
• Record frequency, recency, and affected project context

3. Cluster signals

• Group by: domain (python/js/rust/docs/tooling), command lineage, and error signature.
• Deprioritize one-off sessions with low recurrence.

4. Map to existing skills

• Compare candidate clusters with available skills by `name` and `description`.
• If overlap is high, propose **skill update** path.
• If no overlap, propose **new skill**.

5. Emit ranking output

• Provide `impact`, `frequency`, `confidence`, `skill-fit`, and first-apply command set.

6. Produce minimal first-iteration output for high-priority candidates

• Candidate title + scope
• Trigger phrase examples
• Required inputs
• Suggested workflow summary
• Evidence snippets (line/file-level)
• Suggested dependencies/tools (e.g., `jq`, `rg`, shell utilities, MCP resources)
• Return this through chat/stdout by default. Create a persistent artifact

root only when the user selects one or another required workflow declares it, with file/byte budgets and source/input identity. 7. Optional extension to personal-signal sources

• Only after explicit approval to read personal channels.
• If MCP is available and user has granted access, run MCP resource discovery and include message-signal-derived patterns.
• Keep this opt-in and isolated from coding-signal output unless user requests a merged plan.

Guardrails

• Never infer or emit private content from message logs unless explicitly permitted.
• Skip binary/corrupt files and summarize only parseable text sources.
• Prefer deterministic commands and small scripts over ad-hoc manual parsing.
• Always avoid proposing skills with unresolved operational context (credentials, environment, private URLs).
• If evidence is ambiguous, return `confidence: low` and request one more session sample.
• Reuse one canonical identity-matched inventory instead of materializing

duplicate large extracts. Apply the `$operations-worktree` task artifact contract when retention or resumable phase state is required.

Outputs

• `skill_candidates.md`-style report in chat:
• `reuse` candidates (existing skill can be extended)
• `new` skill candidates (not yet covered)
• top source anchors with references
• recommended next action (create/update)

Read `references/sources.md` for source precedence. Read `references/scorecard.md` for prioritization rules.

Flow

stateDiagram-v2
    [*] --> SelectAuthorizedSources
    SelectAuthorizedSources --> NormalizeAndCluster
    NormalizeAndCluster --> CompareExistingSkills
    CompareExistingSkills --> ProposeUpdate: substantial overlap
    CompareExistingSkills --> ProposeNewSkill: no existing coverage
    CompareExistingSkills --> ReportUncertainty: insufficient evidence
    ProposeUpdate --> RankAndReport
    ProposeNewSkill --> RankAndReport
    RankAndReport --> [*]
    ReportUncertainty --> [*]
    note right of SelectAuthorizedSources
        Personal channels require explicit approval.
        Return findings inline unless retention is selected.
    end note