Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tt-a1i/matt-skills-with-to-goal --skill goal-craftergit clone --depth 1 https://github.com/tt-a1i/matt-skills-with-to-goalWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tt-a1i/matt-skills-with-to-goal/goal-crafter)<a href="https://agentmods.dev/skills/tt-a1i/matt-skills-with-to-goal/goal-crafter"><img src="https://agentmods.dev/badge/skills/tt-a1i/matt-skills-with-to-goal/goal-crafter/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tt-a1i/matt-skills-with-to-goal/goal-crafter"><img src="https://agentmods.dev/badge/skills/tt-a1i/matt-skills-with-to-goal/goal-crafter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 14 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 29 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 117 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00113 | $0.02137 |
| Opus 5 | $0.00056 | $0.01069 |
| Sonnet 5 | $0.00023 | $0.00427 |
| Haiku 4.5 | $0.00011 | $0.00214 |
Grade A, and why
goal-crafter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal Crafter
Turn a vague task into a verifiable goal that an AI agent can run unattended.
Leading principle: A goal without a checkable completion criterion is just a wish. The agent must be able to answer "Am I done?" without asking a human.
Invocation modes
Choose the mode before following the process:
- Standalone mode: the user brings a vague task or directly asks for a goal. Run Phase 1 and clarify the task one question at a time.
- Compiled-handoff mode: an upstream skill such as
to-goalinvokes this skill afterto-spec,to-tickets, ortriage. The approved spec, selected ticket, tracker evidence, and repository state supply the answers. Do not interview the user again. Apply only this skill's verifiability rules and target-harness formatting.
In compiled-handoff mode, if a required product decision or completion condition is genuinely absent from the sources, report that the source is not agent-ready and name the missing evidence. Do not reopen the planning interview from inside goal compilation.
Process
Phase 1 — Clarify the task
Run this phase only in standalone mode. In compiled-handoff mode, extract the five answers from the upstream evidence without asking questions.
Ask the user, one question at a time, in this shape (standalone interview only — keep compiled-handoff mode emoji-free):
❓ **QN** - **<short title>**
<body>
💡 <your recommended answer, when you have one>
Walk these five in order:
-
What exactly should the agent do? Get the task in one sentence. If it's vague ("优化代码", "改进 UI"), push for specifics.
-
Where does it run? Which project / repo / workspace? Is there a specific branch or file area?
-
What does DONE look like? This is the most important question. Push for observable, machine-checkable conditions:
❌ Vague (bad) ✅ Verifiable (good) "代码质量提高" " tsc --noEmit0 errors +eslint0 warnings""UI 更好看" "页面在 375px / 768px / 1440px 三个断点下视觉一致，无溢出" "修复所有 bug" " npm test全部通过，且git diff只包含修复相关改动""写好文档" "README.md 包含安装/使用/API 三个章节，每个章节有代码示例" "性能优化" "Lighthouse Performance 分数 ≥ 90，LCP < 2.5s"
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 208 lines · 113 tokens per session scan A 378f4c526746
goal-crafter is a skill published in the GitHub repository tt-a1i/matt-skills-with-to-goal (160 stars, last pushed 15d ago), licensed MIT. It adds 113 tokens to every session and 2,137 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
projectatlas
Use ProjectAtlas as the atlas-first orientation layer before broad source reads, with MCP-first task startup, short-alias worktree registration and routing, safe targeted initialization, ranked navigation, exact or federated graph evidence, purpose curation, health, lint, and repository-wide token reporting.
codex-coding-plugin
Build, review, or fix ProjectAtlas plugin/runtime installer integration for Codex, Claude Code, and OpenCode, especially version convergence, stale ProjectAtlas cache repair, MCP config generation, skill artifacts, host smoke tests, and fake-host tests for ProjectAtlas releases.
breaking-down-the-work
Splits scope into a product-first work breakdown that follows the 100% rule, keeps pieces from overlapping, uses outline numbers, and gives every piece a dictionary entry. Use when an epic, feature, or new subsystem needs a clean split into deliverables, or one source of truth before folders or work begin. Do not use…
staying-on-mission
Tests the current work against a written, lasting mission anchor and forces one choice, re-anchor, escalate, or stop. Use when an agent keeps finishing tasks but the work drifts from the goal, scope creeps, the same action repeats in a loop, or standards slip one small step at a time. Do not use for a tiny edit with…
closing-stale-packets
Brings an abandoned or half-filled change packet to an honest terminal state by completing it, closing it with a recorded rationale, or deleting it. Use when ng status flags a scaffold or invalid packet, a long session left a draft behind, or work was abandoned mid-packet. Do not use for an actively in-progress…
learning-from-experience
Turns incidents, near misses, bad handoffs, review surprises, escaped bugs, and signals from real use into lasting fixes to your safeguards. Use after something went wrong or nearly did and a future safeguard should change. Do not use during a live incident, which comes first, or to blame someone.