Skip to content
Agentmart
Submit a tool

goal-writer

Draft or review minimal, testable goals.

Skill by Astro-Han

IndexedMIT★ 12
Write a review

Chalk Labs

Need help deploying goal-writer?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/astro-han-goal-writer

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Draft or review minimal, testable goals. Use only when the user explicitly asks to write, revise, or review a goal.

Use cases: writing

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Nov 1, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/goal-writer

What's inside

Skill name
goal-writer
Description
Draft or review minimal, testable goals. Use only when the user explicitly asks to write, revise, or review a goal.
License
MIT
Instructions
38 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (3)

  • SKILL.md
  • cdc-case.md · references/
  • lint_goal.py · scripts/

SKILL.md (first lines)

# Goal Writer

Turn rough intent into the smallest copy-ready execution contract that makes completion decidable. Produce the contract; do not activate it unless explicitly asked.

## Draft

1. Look up facts in the request, named sources, and available environment instead of asking or inventing them. Ask only for user-owned decisions that materially change the contract; state reversible assumptions.
2. Preserve the requested outcome. Do not invent limits or substitute a safer intermediate objective.
3. Write one coherent acceptance decision containing the observable result that should exist and the criterion for accepting it as complete.
4. Add another fact only when deleting it would change the goal's meaning, authorization, or real-world risk. State the boundary directly instead of creating a field for it.

Define acceptance before execution. Completion requires evidence that every necessary condition holds; partial progress is not completion.

For open-ended research or long search tasks, read [the CDC prompt case](references/cdc-case.md) to see how a real goal excludes plausible false completions and governs evidence-seeking iteration.

## Examples

A routine goal can be one sentence:

```text
修复登录超时后的错误跳转;完成以新增回归测试通过且正常登录测试仍通过为准。
```

A real authorization boundary earns one additional sentence, not a new template:

```text
Prepare the customer-data migration and make its dry run pass against the approved fixture with a reviewed rollback plan. Do not execute the production migration without explicit approval.
```

The examples show required meaning, not required structure. Domain workflows belong to the relevant task skill and repository instructions.

## Output and validation

Aim for at most 1000 characters. Return only the contract unless a consequential assumption must be disclosed or the user asks for explanation.

Run `python3 scripts/lint_goal.py -` with the contract on stdin, or pass one or more files. The linter rejects empty contracts, explicit placeholder tokens, and text over 4000 characters; it warns above 2000. Use `--max-chars N` when the target has a stricter hard limit.

From Astro-Han/skills, MIT.

More from Astro-Han/skills

Signals

Stars
12
Forks
3
Open issues
0
Last commit (this folder)
Aug 21, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from Astro-Han

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get goal-writer running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying goal-writer?

CallGet help
Cite this page

goal-writer skill. Agent Mart. https://agentmart.dev/skills/astro-han-goal-writer (last updated 2026-10-24)