prior-art-scout

prior-art-scout is a skill for Claude Code, Codex from tlzmw001/naiyue-skills. It costs 238 tokens per session (4,153 once invoked), scanned A, original, MIT.

A pre-development research skill for finding existing tools, projects, and technical approaches related to a proposed idea. It searches sources such as GitHub, websites, and X, then organizes the findings by the parts of the workflow they cover.

In plain words
What is it for?
Use it before starting a project when you want prior-art research, competing approaches, or evidence about technical feasibility. It produces a traceable evaluation of candidates and recommendations.
Why use it?
It helps you learn whether someone has already built a similar solution and what problems those approaches have encountered. This can inform whether to reuse, adapt, or avoid a direction.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it before starting a project when you want prior-art research, competing approaches, or evidence about technical feasibility. It produces a traceable evaluation of candidates and recommendations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tlzmw001/naiyue-skills/prior-art-scout
Install

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.

Any agent
npx skills add tlzmw001/naiyue-skills --skill prior-art-scout
Clone the repo
git clone --depth 1 https://github.com/tlzmw001/naiyue-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for prior-art-scout

README.md
[![agentmods](https://agentmods.dev/badge/skills/tlzmw001/naiyue-skills/prior-art-scout/github.svg)](https://agentmods.dev/skills/tlzmw001/naiyue-skills/prior-art-scout)
Your own site
<a href="https://agentmods.dev/skills/tlzmw001/naiyue-skills/prior-art-scout"><img src="https://agentmods.dev/badge/skills/tlzmw001/naiyue-skills/prior-art-scout/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.

agentmods 80×15 button for prior-art-scout

Your own site · 80×15
<a href="https://agentmods.dev/skills/tlzmw001/naiyue-skills/prior-art-scout"><img src="https://agentmods.dev/badge/skills/tlzmw001/naiyue-skills/prior-art-scout.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 238 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,153 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00238 $0.04153
Opus 5 $0.00119 $0.02076
Sonnet 5 $0.00048 $0.00831
Haiku 4.5 $0.00024 $0.00415

Measured 12d ago against content hash 33a5b5314642, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

prior-art-scout 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 12d ago.

The scan reads SKILL.md. This mod also ships 18 executable files (scripts/gh_fetch.sh, scripts/prior_art_validation/__init__.py, scripts/prior_art_validation/cards.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/prior-art-scout/SKILL.md · 190 lines

How it starts

The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Prior-Art Scout:开工前技术方案调研

回答:别人试图解决什么问题,用什么工具、流程和技术解决;我能否直接使用或借鉴;前人踩过什么坑;多个方案共同还有什么没有解决;基于证据应如何决策?

这是技术方案调研,不是产品热度排行。star、用户量和活跃度只能作为参考信号。

必读契约

执行 Phase 1、3、4、5 时读取 references/research-design.md。其中定义:

  • 先搜完整问题,再按流程环节拆分查询。
  • 用户提供明确方向时,先搜该方向并提高其候选优先级;覆盖其他候选时必须说明原因。
  • 候选发现覆盖不同供应形态;GitHub 同时执行全文和 topic 搜索。
  • 每个来源最多 5 个候选进入深度分析。
  • 前三类选择依据必须先通过可采用性门槛;路线差异和失败证据候选单独标识。
  • 报告先回答决策问题,候选全集放附录。

铁律

  1. 尽力证明“有人做过”。 发现高度重叠的成熟方案是成功,不得为了支持开工而弱化重叠。
  2. 存疑候选不得无记录丢弃。 全部进入卡片;超出深验预算时标为 relevant_not_deep_verified,明确“相关但未深验”,不得伪装成已验证结论。
  3. 每源深验不超过 5 个。 总上限 = 启用来源数 × 5;不足不补,禁止突破上限。Phase 4 前必须运行 scripts/validate_workspace.py。
  4. 淘汰必留痕。 different_domain 写入 rejected.json,必须说明“它解决 X,我的问题是 Y”。
  5. 每个判断挂证据。 成熟性、核心机制、失败路线、可借鉴点和建议必须引用 raw/、cards/ 或 clones/ 中的具体路径。
  6. 判路线不可行必须有死因证据。 需要弃坑声明、Issue 失败讨论或明确技术瓶颈;项目停更不等于路线不可行。
  7. 成熟/借鉴结论必须深验。 mature_reference 和 partial_borrow 只能授予 selection.json 中已入选且 deep_verified=true 的候选;GitHub 候选必须 clone 并读核心代码,不能只转述 README。
  8. 两个确认点必须真正停下。 用户明确确认前禁止继续下一阶段。
  9. 区分“已踩坑”与“尚未解决”。 已踩坑必须有具体发生记录;共性未解问题必须至少由两个深验候选的证据共同支持。只能写“本轮深验方案中尚未解决”,不得从有限样本推导“行业无法解决”。
  10. 用户方向优先但不免证。 方向查询先执行;方向候选相关性或证据不足时可以降级,但必须留下 priority_override_reason,不得因用户提到就直接判成熟。
  11. 广搜不等于多读。 初搜只抓轻量元数据;GitHub 不在发现阶段批量读取 README/commit/Issue。只有每源最多 5 个入选候选进入 clone 或一手材料深验。
  12. 区分客户端与后端。 开源 SDK 连接闭源服务时标为 open_client_closed_backend,不得写成开源抓取实现。
  13. 前三类先证明能用。 用户方向、完整方案、流程补位候选必须在入选前证明当前有可用产物、使用文档详细且接入复杂度不是 extreme/unknown;否则不能靠这三类理由占用深验名额。
  14. Web 优先使用宿主原生搜索。 读取 adapters/web.md;source=web,实际后端写入 provider,MCP 只作为 transport。宿主无搜索时不得假装执行,也不得自动安装 MCP、索要新 key 或静默切换 provider。
  15. X 默认走 TikHub 但仍是弱证据。 读取 adapters/x.md;TikHub 负责可复现抓取,不把帖子自述升级为事实。线上 OpenAPI、真实响应和一手落地链接优先于 SDK 宣称。

工作区

research/<项目名>/
├── queries.json        # 锚点、任务环节、分来源查询;确认点 1
├── raw/<源>/           # 适配器原始结果
├── candidates.json     # 全量归一化候选
├── cards/              # 每候选一张卡
├── selection.json      # 每源最多 5 个深验候选及选择理由
├── rejected.json       # 问题域不同的候选
├── clones/             # GitHub 深验 clone
└── report.md           # 聚焦决策的最终报告;确认点 2

Read the full file on GitHub · 190 lines

Changes

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.

  1. 12d ago First seen · 190 lines · 238 tokens per session scan A 33a5b5314642

Subscribe to this mod's changes

prior-art-scout is a skill published in the GitHub repository tlzmw001/naiyue-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 238 tokens to every session and 4,153 once invoked, about $0.0012 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 2026-08-31.

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