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 agentmods add skills/smallnest/goal-workflow/code-to-specnpx skills add smallnest/goal-workflow --skill code-to-specgit clone --depth 1 https://github.com/smallnest/goal-workflowWhat 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 | $0.00081 | $0.02398 |
| Opus 5 | $0.00041 | $0.01199 |
| Sonnet 5 | $0.00016 | $0.00480 |
| Haiku 4.5 | $0.00008 | $0.00240 |
Grade A, and why
code-to-spec 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 2d 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.
This is a copy
100% identical to code-to-spec — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.
to-spec — Reverse-Engineer Project Specification
Analyze an existing codebase and produce a structured SPEC document that captures what the project does, how it's built, and what contracts it exposes. The output is a living specification that could be used to rebuild the project from scratch or onboard new contributors.
When to Use
- You want a comprehensive understanding of an existing project
- Onboarding new team members who need a high-level overview
- Documenting a project that was built without a spec
- Comparing actual implementation against intended design
- Preparing for a rewrite or major refactor
- Auditing what a project actually does vs. what people think it does
The Job
- Scope confirmation — ask user what to analyze (entire repo, specific directory, or specific aspect)
- Deep scan — systematically read project structure, entry points, config, tests, and core logic
- Synthesize — produce a structured SPEC document
- Review — present to user for feedback and iteration
- Save — write final SPEC to agreed location
Step 1: Scope Confirmation
Before scanning, ask the user:
What should I analyze?
A. Entire repository (recommended for small-medium projects)
B. Specific directory or module: [path]
C. Specific aspect only (e.g., API surface, data model, auth flow)
Depth level:
1. Overview — high-level architecture + tech stack + key features (fast, ~5 min)
2. Standard — includes API contracts, data models, config, dependencies (default)
3. Deep — adds internal module interactions, error handling patterns, test coverage analysis
If the project is large (>500 files), recommend starting with Overview or a specific module.
Step 2: Deep Scan
Systematically analyze the following (adapt to what exists):
2.1 Project Identity
package.json,go.mod,Cargo.toml,pyproject.toml,pom.xml, etc.- README, LICENSE
- Git history (first commit date, recent activity, contributor count)
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.
- 2d ago First seen · 342 lines · 81 tokens per session scan A 523fd108b00d
code-to-spec is a skill published in the GitHub repository smallnest/goal-workflow (268 stars, last pushed 6d ago), licensed MIT. It adds 81 tokens to every session and 2,398 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to code-to-spec, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
criticism-self-criticism
触发：当一项工作已经完成、进入阶段验收、收到批评反馈，或反复出现同类错误需要系统纠偏时调用；常见信号包括 review、audit、retrospective、quality check、纠错与复盘。 English: Trigger after delivery or at a review checkpoint when quality must be examined honestly and errors must be corrected without defensiveness. Use this skill for structured self-review, feedback processing, and…
mass-line
触发：当你需要收集多方意见、把零散反馈整合成可执行方案，或把方案带回真实使用者/执行者验证时调用；常见信号包括 stakeholder input、user feedback、意见汇总、对齐与验证。 English: Trigger when input must be gathered from many people, synthesized into a clearer plan, and returned to the affected users or executors for validation. Use this skill for a collect-synthesize-validate loop.
workflows
触发：当你面临的任务明显需要多个思想武器协作时调用；常见信号包括：从零启动新项目、攻坚复杂疑难问题、对已有方案进行迭代优化。此 skill 提供标准化的跨 skill 工作流组合，解决"应该先用哪个 skill、怎么衔接"的问题。 English: Trigger when a task clearly requires multiple skills in sequence. Use this skill to select a standard workflow that chains skills together, defines data handoff between steps, and specifies…
concentrate-forces
触发：当多个任务同时争夺时间、注意力、算力或预算，必须确定主攻方向并停止分散用力时调用；常见信号包括优先级过多、资源紧张、推进分散、需要决定先做什么。 English: Trigger when limited resources are being split across too many tasks and one main target must be chosen. Use this skill to concentrate effort, sequence work decisively, and finish a meaningful breakthrough before expanding.
investigation-first
触发：当你准备下判断、做决策或提出建议，但事实、上下文或一手信息还不充分时优先调用；常见信号包括 unknowns、信息缺口、证据不足、领域陌生、需要先摸清现状。 English: Trigger before making claims or decisions when context is incomplete, evidence is weak, or the domain is unfamiliar. Use this skill to investigate first, gather firsthand facts, and let reality shape the conclusion.
overall-planning
触发：当你需要在多个目标、利益方或相互制约的指标之间做动态平衡时调用；常见信号包括 trade-offs、目标冲突、系统性约束、优化一项会伤害另一项。 English: Trigger when several important goals must be advanced together and optimizing one dimension can damage another. Use this skill to map the key relationships, avoid one-sided decisions, and balance the system as a whole.