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 joenandez/spectre --skill spectre-kickoffgit clone --depth 1 https://github.com/joenandez/spectreWrote 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/joenandez/spectre/spectre-kickoff)<a href="https://agentmods.dev/skills/joenandez/spectre/spectre-kickoff"><img src="https://agentmods.dev/badge/skills/joenandez/spectre/spectre-kickoff/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/joenandez/spectre/spectre-kickoff"><img src="https://agentmods.dev/badge/skills/joenandez/spectre/spectre-kickoff.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00090 | $0.01210 |
| Opus 5 | $0.00045 | $0.00605 |
| Sonnet 5 | $0.00018 | $0.00242 |
| Haiku 4.5 | $0.00009 | $0.00121 |
Grade A, and why
spectre-kickoff 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 yesterday.
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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
kickoff
Deep research entry point: investigate the codebase and external best practices, then hand off a written kickoff doc with a gap analysis and MVP path. Clear on WHAT to produce; the research method is yours.
Inputs
$ARGUMENTS— the project/feature context (the current command arguments). If empty, ask the user for it before any tools.- Optional explicit managed feature name/root or an artifact beneath one.
- Any docs the user references — read them FULLY in main context (not via subagent): vision, constraints, decisions, open questions.
Working set (late-bound — read at runtime, never inline)
- Codebase, via read-only research agents (see Method).
FEATURE_ROOT = .spectre/features/<feature-name>/, resolved from the input or proposed below; current git commit/branch for metadata + permalinks.
Feature root contract
- Reuse a managed
FEATURE_ROOTonly when explicit/current-thread evidence ties it to this work (physical directory wins; never branch/recency/lifecycle/scans); distinct work ignores ambient roots. Otherwise, including on collision, standalone MUST first load and followSkill(spectre-feature-root)through DONE; orchestrated calls escalate. Keep writes beneath it and pass it unchanged.
Method / guardrails
-
Acknowledge first. Open with a reply naming what we're exploring, the proposed feature name/root, the decision we're heading toward, and what success looks like. No tool calls in this first turn.
-
Decompose the project into research areas (components, dirs/files, patterns, data flows, code to extend); track them with TodoWrite.
-
Research in parallel, read-only — locator → analyzer-on-findings → breadth. Spawn follow-ups if a thread is shallow. Use Context7 MCP for central 3rd-party libs.
Agent Task Required output @spectre_finderrelevant files, entry points, handlers, models file paths by domain @spectre_analystdata flow, dependencies, behavior, edge cases file:line for ALL findings @spectre_patternssimilar impls, patterns to follow/avoid code examples w/ file:line @spectre_web_researchbest practices, prior art, pitfalls findings WITH links
What ships with it
1 file 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.
- yesterday Changed · +2 lines 79997399cb36
- 5d ago Changed 0944e1e68c17
- 11d ago First seen · 61 lines · 90 tokens per session scan A 6f0259dbeaa9
spectre-kickoff is a skill published in the GitHub repository joenandez/spectre (161 stars, last pushed yesterday), licensed MIT. It adds 90 tokens to every session and 1,210 once invoked, about $0.0005 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.
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