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-researchgit 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-research)<a href="https://agentmods.dev/skills/joenandez/spectre/spectre-research"><img src="https://agentmods.dev/badge/skills/joenandez/spectre/spectre-research/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-research"><img src="https://agentmods.dev/badge/skills/joenandez/spectre/spectre-research.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 | $0.00115 | $0.01000 |
| Opus 5 | $0.00057 | $0.00500 |
| Sonnet 5 | $0.00023 | $0.00200 |
| Haiku 4.5 | $0.00012 | $0.00100 |
Grade A, and why
spectre-research 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
research
Codebase research: spawn parallel read-only agents, synthesize their findings into one evidence-based document. Live code is the source of truth.
Inputs
- Research question / topic (from
$ARGUMENTS). If absent, send an immediate reply asking for it and stop. - Optional explicit managed feature name/root or an artifact beneath one.
- Any files the user names (tickets, docs, JSON).
Working set
FEATURE_ROOT = .spectre/features/<feature-name>/, resolved from the input or chosen autonomously below. Read branch/commit/repo metadata via tool at write time, never inline earlier.- Agents (read-only, run in parallel):
@spectre_finder(where code lives),@spectre_analyst(how it works),@spectre_patterns(similar implementations),@spectre_web_research(3rd-party docs — instruct it to return LINKS). Context7 MCP only if the user explicitly asks for library docs.
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
- Immediate reply first — acknowledge the topic and state the feature name/root the workflow will use (or ask for the topic) with NO tool calls in the opening turn.
- Read named files fully in main context (no limit/offset) before decomposing.
- Decompose the question into areas; track with TodoWrite. Strategy: locate → analyze promising hits → fan out parallel reads. Tell each agent what to find, not how to search.
- Wait for ALL agents before synthesizing. Compress each return to a 1–2K summary; do not write per-agent scratch files.
- Synthesize: prefer live-code findings as source of truth; connect findings across components; cite concrete
path:line; answer the user's actual question with evidence.
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 · +5 lines 689bb8049326
- 6d ago Changed 77f3a49b381c
- 7d ago Changed 6e1f5f971d8c
- 11d ago First seen · 47 lines · 115 tokens per session scan A f2cdea248202
spectre-research is a skill published in the GitHub repository joenandez/spectre (161 stars, last pushed 2d ago), licensed MIT. It adds 115 tokens to every session and 1,000 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.
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