Agent skill

Goalcraft

by grp06 in grp06/goalcraft

Turn a rough draft, vague ambition, or messy task brief into a powerful Codex /goal objective for persistent, evidence-checked work.

MITAuto-check passedTesting & QA

Install Goalcraft

skills CLI
$ npx skills add grp06/goalcraft --skill goalcraft -a claude-code

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

GitHub CLI
$ gh skill install grp06/goalcraft goalcraft --agent claude-code

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

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

Facts

Skill name
goalcraft
GitHub stars
102
Token cost
~3.8k tokens
SKILL.md length
1,963 words
Files
7 (incl. scripts, references, assets)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Turn a rough draft, vague ambition, or messy task brief into a powerful Codex /goal objective for persistent, evidence-checked work.

  • Works in 11 steps: Decide whether a Goal is the right tool. → Identify the rough objective, workspace,… → Shape the goal around evidence, not… → …
  • The user asks to write
  • SKILL.md covers Core Contract, Workflow, Output Format and Quality Bar
  • Runs Python scripts from its folder; calls python3

What it does

Goalcraft is an agent skill from grp06/goalcraft. Turn a rough draft, vague ambition, or messy task brief into a powerful Codex /goal objective for persistent, evidence-checked work. Use when the user asks to write, improve, format, sharpen, stress-test, or activate a Codex goal, thread goal, durable goal, or /goal prompt.

Its SKILL.md is about 3.8k 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 `README.md`, `agents/openai.yaml` and `references/codex-goal-contract.md`).

It sits in Testing & QA, covering Load testing. The repository describes itself as: A codex skill to write great /goal prompts ⭐️ star if you like it! ⭐️. The licence is MIT.

When your agent uses it

  • The user asks to write
  • Activate a Codex goal

Example prompts

  • “/goalcraft”

Requirements

  • Python 3

Workflow steps

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

  1. Decide whether a Goal is the right tool.
  2. Identify the rough objective, workspace, and expected end state.
  3. Shape the goal around evidence, not effort. Use these six fields as the main drafting spine.
  4. Add supporting details only when they improve the contract.
  5. Design the feedback loop before drafting the final goal.
  6. For research or investigation goals, define the evidence standard before the work begins.
  7. Keep the objective usable by Codex.
  8. Choose the output shape.
  9. Validate length before activation.
  10. Activate the goal.
  11. Decide output mode.

What it can do on your machine

Read from SKILL.md and the folder at commit e507e41. 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 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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

Goalcraft loads about 3.8k tokens when it runs, and up to ~4.9k if it reads all its reference files. Until then it costs about 71 tokens; SKILL.md has 1,963 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~71
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.9k

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 grp06/goalcraft at commit e507e41, republished under its MIT licence (© grp06). 1,963 words, ~3,822 tokens.

Download SKILL.mdSave it as .claude/skills/goalcraft/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
goalcraft
description
Turn a rough draft, vague ambition, or messy task brief into a powerful Codex /goal objective for persistent, evidence-checked work. Use when the user asks to write, improve, format, sharpen, stress-test, or activate a Codex goal, thread goal, durable goal, or /goal prompt.

Goalcraft

Core Contract

Convert messy intent into a compact Codex /goal objective and activate it: a thread-scoped, user-controlled completion contract that persists until evidence says the work is complete or honestly blocked. A strong goal defines a closed loop: choose the next action, run it, score progress against an explicit evaluator or checklist, record the result, then continue or stop based on evidence. Treat the /goal as a launcher, not the full plan: the objective must be less than 4,000 characters, but if it fits under that hard limit, activate it instead of repeatedly shortening it. Goalcraft's default final result is an active goal, not merely a ready-to-paste draft. Only skip activation when the user explicitly asks for draft-only, review-only, planning-only, or says not to set/start the goal.

For current Codex /goal mechanics, read references/codex-goal-contract.md when the exact runtime behavior matters.

Workflow

  1. Decide whether a Goal is the right tool.

    • Use a Goal when the work has a durable objective, an evidence-based finish line, and a path that may require several turns of investigation or iteration.
    • Do not recommend a Goal for a one-line edit, simple explanation, short code review, or a request where the user wants one answer and then a stop.
    • If the finish line is vague, recommend a goal-sharpening pass before activation rather than drafting a broad objective like "make this better."
  2. Identify the rough objective, workspace, and expected end state.

    • If the user supplied a draft, preserve their intent and tighten it.
    • If a repo or files are mentioned, inspect them before finalizing the goal.
    • If a critical success criterion is missing, ask the smallest necessary question; otherwise state assumptions.
  3. Shape the goal around evidence, not effort. Use these six fields as the main drafting spine.

    • Outcome: what must be true at the end.
    • Verification surface: the tests, benchmark, report, artifact, logs, command output, source material, screenshots, or explicit confirmation that proves it.
    • Constraints: what must not regress while Codex works.
    • Boundaries: which files, directories, systems, tools, data, repositories, or resources Codex may use.
    • Iteration policy: how Codex should choose the next useful action after each attempt.
    • Blocked stop condition: when Codex should stop, what evidence to report, and what input would unlock progress.
  4. Add supporting details only when they improve the contract.

    • Starting point: current context, repo, branch, artifact, issue, or known state.
    • Deliverables: concrete artifacts such as code paths, tests, PRs, reports, screenshots, or logs.
    • Approval boundaries: destructive actions, credentials, deploys, commits, messages, purchases, or other user-controlled decisions.
    • Checkpoint rhythm: how often to test, review, summarize progress, or pause.
    • Success metric: the observable result that proves completion.
    • Realistic environment: production-like preview, matching flags/config, representative data, authenticated browser session, real device, or other surface needed for evidence to mean what the goal says it means.
    • Progress surface: attempt ledger, current-state summary, draft PR, meaningful commit cadence, status artifact, update channel, or side-chat-readable status when the work may run for hours or days.
  5. Design the feedback loop before drafting the final goal.

    • Identify the score: metric, checklist, test result, scorecard, artifact count, benchmark, manual-review packet, or other evidence that lets Codex decide whether progress improved, stalled, or completed.
    • For measurable goals, prefer a baseline, target, measurement method, and counter-metric or anti-gaming guardrail. For example, test pass-rate goals should not be achieved by reducing meaningful coverage.
    • Prefer a fast iteration evaluator plus a slower final gate. For example: cheap smoke test, subsampled eval, lint/typecheck, focused replay, or checklist during work; full suite, full replay, deploy check, visual review, or final report before done.
    • For environment-sensitive goals, name the closest realistic environment Codex may use. If it cannot access one, either make environment setup the preliminary goal or require proxy results to be labeled as such.
    • For visual goals, treat images as context unless image matching is explicitly the requirement. Define completion through feature checklist, design-system adherence, interaction behavior, accessibility, and visual-diff tooling when appropriate; do not allow shortcuts such as cropping or inlining the reference image to fake fidelity.
    • For multi-hour or multi-day goals, name or recommend durable tracking surfaces: a current plan/queue, experiment or attempt ledger, decision/rejection log, scratchpad or daily notes, and generated current-state summary when useful.
    • For long-running implementation goals, consider whether commits, a draft PR, deploy preview, status artifact, or update channel should be part of the control loop.
    • If the real goal cannot yet be measured, recommend a preliminary goal to create the checklist, evaluator, scorecard, or tracking files before starting the main continuation loop.
    • Treat tracking files as part of the control loop, not optional documentation. They should help the next agent choose the next action without rereading the full conversation.
  6. For research or investigation goals, define the evidence standard before the work begins.

    • Ask for a claim inventory and evidence map when the task involves reproducing, auditing, or investigating uncertain source material.
    • Require the final artifact to separate confirmed findings, approximate reconstructions, support-only evidence, blocked claims, and remaining uncertainty.
    • If exact proof may be unavailable, say how proxy evidence should be labeled instead of letting a plausible artifact become an overclaimed conclusion.
  7. Keep the objective usable by Codex.

    • Hard limit: the objective text after /goal must be less than 4,000 characters.
    • Return the goal as soon as it fits under the hard limit.
    • Do not impose a lower working maximum such as 3,800 characters.
    • Treat only objectives of 4,000 characters or more as failed drafts.
    • The /goal should be the compact execution contract. Put rationale, examples, candidate lists, detailed scorecards, and nonessential context in companion notes outside the /goal payload.
    • Make every requirement auditable against files, commands, PR state, logs, screenshots, or explicit user confirmation.
    • Include score-loop and tracking-file detail in the /goal only when execution-critical; otherwise put detailed evaluator/checklist/memory structure in companion notes or a referenced repo document.
    • Include baseline, target, anti-gaming, realistic-environment, visual-completion, progress-surface, and cleanup-gate details in the /goal only when they are execution-critical; otherwise put them in companion notes.
    • Include exact commands only when they are already known from the repo or user.
    • Avoid hidden flags in slash text. /goal --tokens 50K ... is literal objective text in the TUI, not parsed syntax.
    • If a token budget is requested, present it separately from the objective text unless the target surface supports a separate budget field.
    • For complex or ambiguous work, recommend a planning/interview pass before setting the goal.
    • For very large work, include subagent/orchestration guidance only when the current Codex environment supports subagents and the work can be split into bounded, reviewable lanes.
  8. Choose the output shape.

    • Always start with compact shape: Outcome, Context, Boundaries, Constraints, Verify, Iterate/done/stop.
    • Do not use the full checklist as output structure unless the user explicitly asks for a verbose draft outside /goal.
    • Do not force every planning concept into the /goal. Reason with the full checklist, then compress related items before output.
    • Merge deliverables into Boundaries.
    • Merge must-not-regress into Constraints.
    • Merge autonomy, checkpoint rhythm, and blocked stop conditions into Iterate/done/stop.
    • Keep examples and candidate lists outside the goal unless they are essential execution constraints.
    • Section soft budgets: Outcome 250, Context 650, Boundaries 900, Constraints 550, Verify 550, Iterate/done/stop 700 characters.
  9. Validate length before activation.

    • Put only the ready-to-paste /goal ... command in a temporary file or pipe it to this skill's bundled validator: resolve scripts/validate_goal_length.py relative to the directory containing this SKILL.md, then run it with --max-chars 3999.
    • The validator belongs to Goalcraft, not to the user's working project. Do not search the user's repository for scripts/validate_goal_length.py.
    • The script strips a leading /goal and counts the actual objective Codex validates.
    • Validate once. If it passes the hard limit, return it. Do not keep running validation or shortening the goal just to satisfy a lower target.
    • If it fails the hard limit, discard the draft and switch immediately to emergency shape: /goal Complete [outcome] within [boundaries]. Preserve [constraints]. Verify with [checks/evidence]. Stop for [risks/blockers]. Done when [criteria].
    • After emergency fallback, validate once against the hard limit using --max-chars 3999.
    • Do not run iterative "make it a little shorter" loops. More than one failed hard-limit validation means the draft shape failed, not the character counter.
    • Do not activate or return a final goal until the validator passes.
    • If the bundled script path is unavailable, use this deterministic fallback on the file containing the exact final /goal ... command:
Show full SKILL.md (581 more words)Show less
bash
python3 - "$GOAL_FILE" <<'PY'
import pathlib, sys
text = pathlib.Path(sys.argv[1]).read_text(encoding="utf-8").strip()
if text.startswith("```"):
    lines = text.splitlines()
    if lines and lines[0].startswith("```"):
        lines = lines[1:]
    if lines and lines[-1].startswith("```"):
        lines = lines[:-1]
    text = "\n".join(lines).strip()
if text.startswith("/goal") and text[len("/goal"):].startswith((" ", "\n", "\t")):
    text = text[len("/goal"):].strip()
count = len(text)
print(f"objective_chars={count}")
if count > 3999:
    raise SystemExit(1)
PY
  1. Activate the goal.
  • Default: after validation, activate the objective with the available goal surface (create_goal, thread/goal/set, or the current environment's equivalent).
  • If a current active goal already exists, do not silently replace it. Report the conflict and ask for confirmation unless the user has explicitly asked to replace the current goal.
  • If the goal tool supports a separate token budget and the user explicitly requested one, pass it as the tool's budget field rather than embedding budget syntax in the objective text.
  • If activation fails, report the exact failure and include the validated /goal ... text as the fallback artifact.
  1. Decide output mode.
  • Default: activate the goal and return a short confirmation with assumptions, objective length, and any companion notes.
  • Draft-only exception: when the user explicitly asks not to activate, return a ready-to-paste /goal ... block plus a short assumptions list.
  • If the user asks for review, critique the draft first and include a revised version.
  • If the user explicitly asks to replace an existing goal, call the goal tool or app-server surface only after the objective is final.

Output Format

Return companion notes outside the goal when details should not spend objective characters. Use this shape by default after successful activation:

markdown
Activated goal:
- Objective length: N characters
- Assumptions: ...

Notes outside the goal:
- ...

For draft-only requests, use this shape:

markdown
Assumptions:
- ...

Draft goal:

/goal Outcome: ...

Context: ...

Boundaries: ...

Constraints: ...

Verify: ...

Iterate/done/stop: ...

Objective length: N characters

Notes outside the goal:
- ...

Omit companion notes only for trivial goals. For nontrivial goals, prefer a short activated objective plus useful companion notes over a long objective. Do not put assumptions, rationale, candidate lists, or optional details inside the /goal unless they are execution-critical.

Quality Bar

  • The goal should be operationally sharp enough that another agent can continue after compaction or resume.
  • The goal should make the next loop obvious: choose an action, run it, score it, record the result, and continue or stop.
  • For long-running goals, the goal or companion notes should identify the durable state files or generated views that preserve plan, attempts, decisions, and current status.
  • The objective should feel like a compact launcher. If it needs lots of nuance, put that nuance outside the goal or into a referenced file.
  • The goal should make premature completion hard: "done" must require evidence, not intent, elapsed time, budget exhaustion, proxy signals, or passing unrelated checks.
  • The goal should make fake progress hard: preserve meaningful coverage, realistic inputs, real interaction paths, and other counter-metrics that prevent Codex from satisfying the letter of the goal while missing the intent.
  • For research goals, the final output should preserve levels of epistemic support instead of flattening exact reproduction, approximate support, blocked claims, and uncertainty into one success claim.
  • For environment-sensitive goals, evidence should come from the closest realistic environment available; proxy evidence must be clearly labeled.
  • For visual goals, reference images should not become the only exit criterion unless the user explicitly asks for image matching; completion should be anchored to specs, design-system rules, interactions, accessibility, and visual-diff evidence when useful.
  • For long-running implementation goals, completion should include a cleanup/review gate: inspect failed attempts, remove abandoned scaffolding, run the relevant review/tests, and summarize final evidence plus remaining risks.
  • The goal should avoid over-prescribing implementation details unless those details are part of the actual requirement.
  • The goal should preserve user boundaries: planning-only, no edits, no deploys, no commits, or approval requirements must be explicit when present.
  • The final objective should pass this skill's bundled scripts/validate_goal_length.py --max-chars 3999. If it fits under the hard limit, activate it without further shortening. If the normal draft fails the hard limit, use the emergency compact shape and validate once against the hard 3,999-character maximum.

© grp06, 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 the repository root of grp06/goalcraft.

  • SKILL.md
  • LICENSE
  • README.md
  • agents/openai.yaml
  • assets/goalcraft-infographic.png
  • references/codex-goal-contract.md
  • scripts/validate_goal_length.py

Open the folder on GitHubat commit e507e41

Compare with similar skills

Goalcraft 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.

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Go Testingcxuu/golang-skills1701 repos~1.3kAutomated safety check: PassApache-2.0
Thinking Partnermattnowdev/thinking-partner206—~4.4kAutomated safety check: PassMIT
Visionkunchenguid/vision329—~2.9kAutomated safety check: PassMIT
Volt Load TestingowenHochwald/volt141—~1.2kAutomated safety check: PassMPL-2.0

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Categories

Questions about Goalcraft

What does Goalcraft do?

Turn a rough draft, vague ambition, or messy task brief into a powerful Codex /goal objective for persistent, evidence-checked work. Goalcraft is an agent skill from grp06/goalcraft. Turn a rough draft, vague ambition, or messy task brief into a powerful Codex /goal objective for persistent, evidence-checked work.

When should I use Goalcraft?

Goalcraft fits situations like: the user asks to write; activate a Codex goal.

How do I install Goalcraft in Claude Code?

Run `npx skills add grp06/goalcraft --skill goalcraft -a claude-code`. Or copy the skill folder (the grp06/goalcraft repository) into .claude/skills/goalcraft in your project. Claude Code loads it when a task matches its description.

How do I install Goalcraft in Codex?

Run `npx skills add grp06/goalcraft --skill goalcraft -a codex`. Or copy the skill folder (the grp06/goalcraft repository) into .agents/skills/goalcraft in your project. Codex loads it when a task matches its description.

Can I use Goalcraft 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 grp06/goalcraft --skill goalcraft -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/goalcraft, .gemini/skills/goalcraft, .github/skills/goalcraft and .opencode/skills/goalcraft in your project.

What does Goalcraft need to run?

Going by SKILL.md and its folder, Goalcraft needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Goalcraft 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 Goalcraft 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 Goalcraft use?

Goalcraft is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Goalcraft use?

About 3.8k tokens (SKILL.md is roughly 15k 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 1k tokens, read only when the agent opens those files.

What are the alternatives to Goalcraft?

Skills that share tags, products or a category with Goalcraft: Writing Livekit Scenarios (livekit-examples/agent-starter-python, 264 stars), Go Testing (cxuu/golang-skills, 170 stars), Thinking Partner (mattnowdev/thinking-partner, 206 stars) and Vision (kunchenguid/vision, 329 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Goalcraft?

grp06 (a GitHub user) maintains it in grp06/goalcraft, which has 102 GitHub stars. The repository was last updated on June 4, 2026.

Source: grp06/goalcraft on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.