Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/jscraik/Agent-Skillsnpx agentmods add skills/jscraik/agent-skills/goal-governorWrote 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/jscraik/agent-skills/goal-governor)<a href="https://agentmods.dev/skills/jscraik/agent-skills/goal-governor"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/goal-governor/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/jscraik/agent-skills/goal-governor"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/goal-governor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high System Prompt Leakage · line 55 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00064 | $0.01963 |
| Opus 5 | $0.00032 | $0.00981 |
| Sonnet 5 | $0.00013 | $0.00393 |
| Haiku 4.5 | $0.00006 | $0.00196 |
Grade A, and why
goal-governor 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 9d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal Governor
When To Use
Use only for durable Codex goal work that has, or needs, a repo-visible board.
Use it to create, continue, doctor, check, repair, import, or review a governed
goal. Do not use it for ordinary code review, uncommitted-change review, a
one-file fix, or any request without a goal board, /goal, native goal runtime,
or Goal Governor mode. For an ordinary review, do not write
goal-governor-output.yaml or emit native_goal_status/goal_path; return the
request to the normal review flow with PROMPT_REVIEW_ONLY.
Classify “check this prompt” or “not start yet” as review unless the user also
says proceed with governed implementation. Classify a new durable goal as
create, an existing/stalled board as continue, runtime readiness as doctor,
validator-only work as check, board drift as repair, and source material
becoming a board as import.
Inputs
- Project instructions plus a goal prompt or selected board path.
- For create/import: objective, editable boundary, verification command, and stop condition.
- For continuation/closeout:
goal.md,state.yaml,receipts.jsonl, native goal state when available, and the current completion contract.
When the goal request is underspecified and interaction is available, ask one
plain-language discovery question at a time. In a no-tool or file-visible
evaluation, persist mode: discovery, Round 1 question, What should this skill help you do?, and Why this matters in the output contract.
Outputs
Return YAML with schema_version, mode, goal_path, native_goal_status,
board_status, next_action, truth_lanes, receipt_closure_ledger,
continuation_gate, native_blocker_audit, validation_evidence, and risks.
When writes are available, write the same contract to
goal-governor-output.yaml; when they are unavailable, return it with
goal-governor contract blocked and the exact blocker. In review mode, return
prompt readiness only.
Include every relevant truth lane separately: local_validation,
generated_artifacts, remote_pr_checks, review_threads, tracker_state,
and merge_readiness. A passing lane does not infer another lane.
What ships with it
16 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.
- .plugin-evalignore 240 B
- agents/openai.yaml 368 B
- references/contract.yaml 7.2 KB
- references/creation-and-continuation.md 5.6 KB
- references/discovery-interview.md 2.8 KB
- references/evals.yaml 33 KB
- references/goal-contract.md 16 KB
- references/implementation-notes-contract.md 3.6 KB
- references/markers.md 3.4 KB
- references/native-goal-runtime.md 9.4 KB
- references/session-evidence-closeout.md 3.2 KB
- references/task-profile.json 1.2 KB
- scripts/check_goal_board_impl.py 28 KB runs code
- scripts/check_goal_board.py 1.4 KB runs code
- scripts/write_pr_triage_report.py 17 KB runs code
- scripts/write_subagent_handoff_report.py 6.0 KB runs code
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.
- 9d ago First seen · 156 lines · 64 tokens per session scan A 5445fabb4470
goal-governor is a skill published in the GitHub repository jscraik/Agent-Skills (8 stars, last pushed 11d ago), licensed Apache-2.0. It adds 64 tokens to every session and 1,963 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
process-doc
Turn an operational process into a clear SOP, role model, control map, and improvement backlog.
taskuary-setup
Walk the owner through setting Taskuary up - the AI brain, where work arrives, the operator documents, reports and workflows - by reading the install's real state and using the screens that already exist. Use when a task was opened as a Taskuary setup walkthrough.
epic-lead
Use when delivering one approved Kanban EPIC through governed integration, review, and handoff.
teamlead
Use at the START of ANY code task — write/edit/refactor/read code, feature, bug-fix, migration, code investigation. The main thread acts as team-lead, NOT implementer — it delegates work to subagents and surfaces only decisions and results, keeping the main chat clean.
knbn
Alias for the kanban skill. Use when the user invokes or refers to Kanban as "knbn".
foreman-to-issues
Break an approved PRD into small, dependency-ordered, vertically-sliced implementation issues written as local files in the Foreman feature directory. Each issue ships a runnable acceptance check and a declared file footprint. No GitHub, no live quizzing of the user — emits files matching Foreman's issue schema with…