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Agent skill

Codex Goal Mining

by vincentkoc in vincentkoc/dotskills

Mine structured Codex /goal history locally or across a configured machine fleet, measure active goal time and resumed thread spans, identify unfinished and recurring semantic runs, and turn them…

MITAuto-check passed

Install Codex Goal Mining

skills CLI
$ npx skills add vincentkoc/dotskills --skill codex-goal-mining -a claude-code

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

GitHub CLI
$ gh skill install vincentkoc/dotskills codex-goal-mining --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/vincentkoc/dotskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/codex-goal-mining .claude/skills/codex-goal-mining && 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
codex-goal-mining
GitHub stars
107
Token cost
~1.2k tokens
SKILL.md length
505 words
Files
7 (incl. scripts, references, assets)
Skills in repo
19
Repo updated
First seen
Licence
MIT

At a glance

Mine structured Codex /goal history locally or across a configured machine fleet, measure active goal time and resumed thread spans, identify unfinished and recurring semantic runs, and turn them…

  • Works in 7 steps: Collect structured data with… → Treat the data sources correctly. → Report collection coverage first. → …
  • The user asks to inspect goal history
  • SKILL.md covers Purpose, When to use, Workflow and Inputs, plus 1 more section
  • Runs Python scripts from its folder

What it does

Codex Goal Mining is an agent skill from vincentkoc/dotskills. Mine structured Codex /goal history locally or across a configured machine fleet, measure active goal time and resumed thread spans, identify unfinished and recurring semantic runs, and turn them into stable copy-paste rerun suites. Use when the user asks to inspect goal history, summarize goal commands, find repeated goals, recover large beta campaigns, compare goal duration or token usage, or prepare reusable /goal prompts and privacy-scrubbed reports.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `agents/openai.yaml`, `references/fleet-policy.example.json` and `references/goal-suite-patterns.md`).

The repository describes itself as: 🐙 A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns. The licence is MIT.

When your agent uses it

  • The user asks to inspect goal history
  • Summarize goal commands
  • Find repeated goals
  • Recover large beta campaigns

Example prompts

  • “/codex-goal-mining”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Collect structured data with scripts/codex-goal-report.py.
  2. Treat the data sources correctly.
  3. Report collection coverage first.
  4. Mine patterns semantically.
  5. Produce reusable reruns.
  6. Keep reports private.
  7. For retained output or resumable collection state, apply the task artifact

What it can do on your machine

Read from SKILL.md and the folder at commit b83ca13. 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

    Ships 2 files in scripts/ (Python), which the agent can run.

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

  • Network

    No URLs in SKILL.md.

    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

Codex Goal Mining loads about 1.2k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 119 tokens; SKILL.md has 505 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~119
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.6k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from vincentkoc/dotskills at commit b83ca13, republished under its MIT licence (© vincentkoc). 505 words, ~1,219 tokens.

Download SKILL.mdSave it as .claude/skills/codex-goal-mining/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
codex-goal-mining
description
Mine structured Codex /goal history locally or across a configured machine fleet, measure active goal time and resumed thread spans, identify unfinished and recurring semantic runs, and turn them into stable copy-paste rerun suites. Use when the user asks to inspect goal history, summarize goal commands, find repeated goals, recover large beta campaigns, compare goal duration or token usage, or prepare reusable /goal prompts and privacy-scrubbed reports.
license
MIT
metadata.workflow-exemption
Ordered collection, coverage accounting, analysis, and reporting; no separate action-routing lifecycle.
metadata.source
https://github.com/vincentkoc/dotskills

Codex Goal Mining

Purpose

Recover structured Codex goal history and convert free-form runs into evidence-backed, repeatable suites.

When to use

  • The user asks what /goal commands ran locally or across the fleet.
  • Large QA, beta, release, localization, model, cleanup, or PR campaigns need retesting.
  • The user wants active, paused, blocked, or long-running goals ranked.
  • Repeated semantic runs need stable suite names and copy-paste prompts.
  • Goal time, thread span, tokens, dates, machines, or reachability matter.

Workflow

  1. Collect structured data with scripts/codex-goal-report.py.
    • Fleet report: scripts/codex-goal-report.py --policy ~/.config/codex-goal-mining/fleet-policy.json --json --output ~/.codex/reports/codex-fleet-goals.json
    • Local only: scripts/codex-goal-report.py --local --json
    • Recent window: add --since YYYY-MM-DD.
    • Exact activity window: add --activity-overlap --since <ISO> --until <ISO>. Existing --since semantics remain creation-time based without that flag.
    • Bounded repeat snapshots: add --cursor-file <path> to compute reset-safe deltas. No cursor or report directory is created by default.
    • Selected machines: repeat --machine <fleet-alias>.
    • Require fleet coverage with --fleet; any unreachable source is rendered and returns nonzero instead of silently reporting success.
    • Use --one-attempt for a single configured/first interpreter attempt per host. Policy entries may declare python and wsl_python.
    • Start fleet configuration from references/fleet-policy.example.json; never commit a real private inventory.
  2. Treat the data sources correctly.
    • Prefer goals_1.sqlite for objective, status, tokens, and Codex-recorded active goal time.
    • Join state_5.sqlite for thread timestamps and rollout paths.
    • Use JSONL only as a fallback for older installations.
    • Wall-clock thread span includes idle and resume gaps; never describe it as active labor.
    • Goal database counters are lifetime snapshots. Only cursor deltas have an observation interval, and a reset is unknown rather than zero.
    • Preserve root/child identity where the state database supplies it. JSONL fallback reports unknown rather than guessing.
  3. Report collection coverage first.
    • List reached and unreachable machines.
    • Give the date range, goal count, statuses, total active goal time, and median goal time.
    • Preserve exact transport blockers instead of silently shrinking the fleet.
  4. Mine patterns semantically.
    • Exact duplicate text is weak evidence because operators rephrase goals.
    • Cluster by intended test surface, matrix, exit criteria, and repeated operating contract.
    • Prioritize unfinished goals and recurring high-time campaigns.
    • Separate product beta suites from operational queues such as contributor PR sweeps.
  5. Produce reusable reruns.
    • Use [suite:<name>] [baseline:<sha-or-date>] [matrix:<targets>] [exit:<criteria>].
    • Include a fixed matrix, evidence requirements, blocker rules, and definition of done.
    • Start from references/goal-suite-patterns.md, then adapt to current evidence.
  6. Keep reports private.
    • Default to terminal/JSON delivery. Use --output only when retained output was requested or required.
    • Scrub secrets, private hosts, personal absolute paths, and credentials before creating a gist or sharing externally.
    • Use a secret gist unless the user explicitly requests public visibility.
  7. For retained output or resumable collection state, apply the task artifact contract from $operations-worktree. Reuse identity-matched canonical inventories instead of copying large payloads.
Show full SKILL.md (55 more words)Show less

Inputs

  • Local Codex stores under ~/.codex/.
  • Optional fleet policy supplied with --policy or CODEX_FLEET_POLICY.
  • Optional date window, machine aliases, suite focus, or output path.

Outputs

  • Markdown or JSON fleet goal report.
  • Ranked active, paused, blocked, and long-running goals.
  • Semantic campaign summary with timing and reachability caveats.
  • Stable copy-paste /goal suite prompts and rerun priority order.

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

Files

SKILL.md and 6 other files (scripts, references, assets) in skills/codex-goal-mining of vincentkoc/dotskills.

  • SKILL.md
  • agents/openai.yaml
  • assets/icon.jpg
  • references/fleet-policy.example.json
  • references/goal-suite-patterns.md
  • scripts/codex-goal-report-test.py
  • scripts/codex-goal-report.py

Open the folder on GitHubat commit b83ca13

Compare with similar skills

Codex Goal Mining 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.

Codex Goal Mining compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Codex Goal Mining this skillvincentkoc/dotskills107—~1.2kAutomated safety check: PassMIT
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Local Conversation Historydaymade/claude-code-skills1.4k—~2.8kAutomated safety check: PassMIT
LocalizeDonchitos/Claude-Code-Game-Studios26k—~5.2kAutomated safety check: NotesMIT
SEO LocalAgriciDaniel/claude-seo18k—~4.5kAutomated safety check: PassMIT
Local Legal SEO Auditsickn33/agentic-awesome-skills47k2 repos~3.2kAutomated safety check: PassMIT

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Questions about Codex Goal Mining

What does Codex Goal Mining do?

Mine structured Codex /goal history locally or across a configured machine fleet, measure active goal time and resumed thread spans, identify unfinished and recurring semantic runs, and turn them…. Codex Goal Mining is an agent skill from vincentkoc/dotskills. Mine structured Codex /goal history locally or across a configured machine fleet, measure active goal time and resumed thread spans, identify unfinished and recurring semantic runs, and turn them into stable copy-paste rerun suites.

When should I use Codex Goal Mining?

Codex Goal Mining fits situations like: the user asks to inspect goal history; summarize goal commands; find repeated goals; recover large beta campaigns.

How do I install Codex Goal Mining in Claude Code?

Run `npx skills add vincentkoc/dotskills --skill codex-goal-mining -a claude-code`. Or copy the skill folder (skills/codex-goal-mining in vincentkoc/dotskills) into .claude/skills/codex-goal-mining in your project. Claude Code loads it when a task matches its description.

How do I install Codex Goal Mining in Codex?

Run `npx skills add vincentkoc/dotskills --skill codex-goal-mining -a codex`. Or copy the skill folder (skills/codex-goal-mining in vincentkoc/dotskills) into .agents/skills/codex-goal-mining in your project. Codex loads it when a task matches its description.

Can I use Codex Goal Mining 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 vincentkoc/dotskills --skill codex-goal-mining -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/codex-goal-mining, .gemini/skills/codex-goal-mining, .github/skills/codex-goal-mining and .opencode/skills/codex-goal-mining in your project.

What does Codex Goal Mining need to run?

Going by SKILL.md and its folder, Codex Goal Mining needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Codex Goal Mining access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Codex Goal Mining 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Codex Goal Mining use?

Codex Goal Mining is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Codex Goal Mining use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 397 tokens, read only when the agent opens those files.

What are the alternatives to Codex Goal Mining?

Skills that share tags, products or a category with Codex Goal Mining: Goals (codewhale-hq/Codewhale, 41k stars), Local Conversation History (daymade/claude-code-skills, 1.4k stars), Localize (Donchitos/Claude-Code-Game-Studios, 26k stars) and SEO Local (AgriciDaniel/claude-seo, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Codex Goal Mining?

vincentkoc (a GitHub user) maintains it in vincentkoc/dotskills, which has 107 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on October 8, 2026.

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