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 cckyros/goal-acceptance --skill goal-planninggit clone --depth 1 https://github.com/cckyros/goal-acceptanceWrote 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/cckyros/goal-acceptance/goal-planning)<a href="https://agentmods.dev/skills/cckyros/goal-acceptance/goal-planning"><img src="https://agentmods.dev/badge/skills/cckyros/goal-acceptance/goal-planning/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/cckyros/goal-acceptance/goal-planning"><img src="https://agentmods.dev/badge/skills/cckyros/goal-acceptance/goal-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00030 | $0.01160 |
| Opus 5 | $0.00015 | $0.00580 |
| Sonnet 5 | $0.00006 | $0.00232 |
| Haiku 4.5 | $0.00003 | $0.00116 |
Grade A, and why
goal-planning 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 10d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal Planning Skill
When a user gives a multi-step task (implement, fix, refactor, etc.), do NOT
call set_acceptance_criteria directly. Instead, spawn a planning subagent
that explores the codebase, drafts criteria, and checks coverage before
locking.
When to Use
- User says "implement X", "fix Y and verify", "refactor Z" — any task with a verifiable outcome.
- Single-line answers, file reads, explanations: skip this skill.
Workflow
Step 1: Spawn Planning Subagent
Use run_subagent (or equivalent) with subagent_explore profile and this
prompt template:
You are a planning agent. Your job: decompose the task below into
acceptance criteria that are non-overlapping, fully covering, and
individually verifiable.
TASK: {paste the user's original request here}
Do NOT implement anything. Do NOT write code. Only plan.
Phase 1 — EXPLORE:
- Read the relevant source files, configs, and tests.
- Identify every module, function, and interface the task touches.
- Note existing patterns and conventions.
Phase 2 — DRAFT CRITERIA:
- Write acceptance criteria. Each criterion MUST have:
- id: kebab-case, unique (e.g. "core-default-role-agent")
- description: specific and concrete, not vague
- required: true if the goal cannot be achieved without it
- method: one of "command" | "file" | "url" (NEVER "text")
- task_ids: linked task IDs for progress tracking
Phase 3 — GOAL-BACKWARD COVERAGE CHECK:
- List every requirement implied by the task description.
- Map each requirement to the criterion(s) that cover it.
- If any requirement is UNCOVERED, add a criterion for it.
- If two criteria overlap (>80% similar description), merge them.
Phase 4 — VAGUE-VERB CHECK:
- Scan every criterion description for vague verbs:
"implement", "ensure", "handle", "improve", "align", "clean up"
- Replace each with a concrete, verifiable action:
BAD: "implement error handling"
GOOD: "wrap fetchUser in try/catch, return 404 for NotFound"
BAD: "improve performance"
GOOD: "add index on orders.user_id, batch N+1 into JOIN"
Phase 5 — VERIFICATION CHECK:
- Every criterion's method must specify:
- command: the exact command to run (e.g. "pnpm test")
- file: the exact file path to check (e.g. "src/engine.ts")
- url: the exact URL to verify (e.g. "GET /health returns 200")
- "run tests" is NOT sufficient. Specify expected outcome.
- "check it works" is NOT sufficient. Specify observable behavior.
Phase 6 — SUBMIT:
- Call set_acceptance_criteria with the final criteria list.
- Call set_task_plan with the task decomposition.
- Return a summary of the coverage matrix.
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.
- 10d ago First seen · 128 lines · 30 tokens per session scan A 38416cd1abb8
goal-planning is a skill published in the GitHub repository cckyros/goal-acceptance (3 stars, last pushed 13d ago), licensed MIT. It adds 30 tokens to every session and 1,160 once invoked, about $0.0002 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 2026-08-31.
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