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 ronronner02/codepilot-agent --skill spec-compoundgit clone --depth 1 https://github.com/ronronner02/codepilot-agentWrote 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/ronronner02/codepilot-agent/spec-compound)<a href="https://agentmods.dev/skills/ronronner02/codepilot-agent/spec-compound"><img src="https://agentmods.dev/badge/skills/ronronner02/codepilot-agent/spec-compound/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/ronronner02/codepilot-agent/spec-compound"><img src="https://agentmods.dev/badge/skills/ronronner02/codepilot-agent/spec-compound.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 | $0.00032 | $0.14694 |
| Opus 5.5 | $0.00013 | $0.05878 |
| Sonnet 5.5 | $0.00006 | $0.02939 |
| Haiku 4.5 | $0.00003 | $0.01469 |
Grade B, and why
spec-compound scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
chmod 700 "$SCRATCH_DIR" How it starts
The opening of the file, as written. The whole thing — 769 lines — stays where its author put it; the contents beside it link to each section on GitHub.
spec-compound
Document a recently solved problem through role-based research; use parallel subagents only when dispatch is explicitly authorized and callable, otherwise run the same roles inline or serially.
Purpose
Captures problem solutions while context is fresh, creating structured documentation in docs/solutions/ with YAML frontmatter for searchability and future reference. Authorized dispatch can parallelize read-only research; correctness does not depend on it.
Why "compound"? Each documented solution compounds your team's knowledge. The first time you solve a problem takes research. Document it, and the next occurrence takes minutes. Knowledge compounds.
Workflow Contract Summary
- 输入： 一个最近解决且已有可回源验证的单一问题，或该问题带来的 durable project vocabulary。
- 输出：
docs/solutions/下带 provenance、适用范围与失效条件的 learning，以及必要时对CONCEPTS.md的局部补充。 - 硬出口： 问题尚未解决、验证证据不足、一次请求包含多个独立 learning、目标 repo/source owner 不明确，或 promotion gate 不满足时不得写入 durable knowledge。
- 权威： 当前 source/test/log 和已验证 outcome 决定可沉淀事实；LLM 判断复用价值；只有 orchestrator 可写知识资产，dispatch 不授予 mutation。
- 消费者： 后续
spec-plan、spec-work、spec-debug、spec-code-review与项目维护者。
Usage
spec-compound # Document the most recent fix
spec-compound [brief context] # Provide additional context hint
spec-compound mode:headless # Non-interactive run for automations
spec-compound mode:headless [context] # Non-interactive run with context hint
One learning per run. The workflow's grounding, overlap detection, and cross-referencing all assume a single solved problem. When a session produced multiple distinct learnings, run the skill once per learning, sequentially — each run grounds fresh against the tree. Do not batch several learnings through one run and stitch cross-references between the drafts afterward; drafting-context numbering ("Learning 3") leaking into written docs is the failure this rule prevents.
CONCEPTS.md bootstrap requests
What ships with it
19 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.
- assets/resolution-template.md 2.8 KB
- references/agents/best-practices-researcher.md 7.2 KB
- references/agents/data-integrity-guardian.md 3.1 KB
- references/agents/framework-docs-researcher.md 5.5 KB
- references/agents/pattern-recognition-specialist.md 3.6 KB
- references/agents/performance-oracle.md 4.5 KB
- references/agents/security-sentinel.md 4.0 KB
- references/agents/session-historian.md 7.7 KB
- references/concepts-vocabulary.md 6.2 KB
- references/grounding-validation.md 6.2 KB
- references/schema.yaml 8.4 KB
- references/yaml-schema.md 7.6 KB
- scripts/run-python.sh 774 B runs code
- scripts/session-history/discover-sessions.sh 4.2 KB runs code
- scripts/session-history/extract-errors.py 9.7 KB runs code
- scripts/session-history/extract-metadata.py 17 KB runs code
- scripts/session-history/extract-skeleton.py 21 KB runs code
- scripts/validate-doc-claims.py 14 KB runs code
- scripts/validate-frontmatter.py 12 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.
- 1mo ago First seen · 769 lines · 32 tokens per session scan B 4175df37b718
spec-compound is a skill published in the GitHub repository ronronner02/codepilot-agent (0 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 14,694 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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