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 flanliulf/SpecLite --skill speclite-story-review-03-fixergit clone --depth 1 https://github.com/flanliulf/SpecLiteWrote 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/flanliulf/speclite/speclite-story-review-03-fixer)<a href="https://agentmods.dev/skills/flanliulf/speclite/speclite-story-review-03-fixer"><img src="https://agentmods.dev/badge/skills/flanliulf/speclite/speclite-story-review-03-fixer/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/flanliulf/speclite/speclite-story-review-03-fixer"><img src="https://agentmods.dev/badge/skills/flanliulf/speclite/speclite-story-review-03-fixer.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 | $0.00070 | $0.01337 |
| Opus 5 | $0.00035 | $0.00668 |
| Sonnet 5 | $0.00014 | $0.00267 |
| Haiku 4.5 | $0.00007 | $0.00134 |
Grade A, and why
speclite-story-review-03-fixer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
[技能说明] 根据 Story 设计审查评估的结论执行 Story 文档修订,并将修订执行总结追加到评估文档中。是 SR 审查工作流中唯一允许修改 Story 文档的环节。
[核心能力] - 评估驱动修订:严格按照审查评估文件的结论执行修订,不自行扩大修订范围 - 自动定位评估文件:自动扫描并定位最新一轮的审查评估文件 - 双粒度适配:自动从评估文件的 Scope 字段识别粒度,适配 Epic 和 Story 两种模式的修订范围 - 精准定点修订:针对评估确认需要修订的问题逐一处理 - 修订记录追踪:将修订执行总结追加到评估文件的指定章节 - 范围边界控制:Story 模式下仅修改指定 Story 文件,超出范围的修订标记为"超出范围"提醒用户
[执行流程]
路径约定和文件名格式以 references/sr-config.md 为准。
Step 1:定位最新评估文件
- 接收用户指定的 Epic 或 Story 标识
- 读取 `references/sr-config.md` 获取路径约定和双粒度判定规则
- 根据用户输入判定 `$review_scope`
- 按 `$review_scope` 确定 `$sr_dir`
- 按配置中的审查评估文件名格式,扫描 `$sr_dir` 下匹配的文件
- 找到 round 值最大的文件作为修订依据
- 读取该文件的完整内容,提取需要修订的问题列表
- 从 YAML 头部 `Scope` 字段确认粒度
- 生成数据:`$evaluation_file_path`、`$fix_items`(待修订问题列表)
Step 2:制定修订计划
- 根据评估结论中"需要修订"的条目,制定修订计划
- 按优先级排序修订顺序
- 确认每个修订项的:
- 涉及的 Story 文件和章节
- 具体修订方案
- 预期效果
- 范围控制:
- Epic 模式:可修改该 Epic 下多个 Story 文件,以及必要时的 Epic 定义文件和架构文档
- Story 模式:仅修改该单个 Story 文件;如评估指出需修改 Epic 文件或架构文档,标记为"⚠️ 超出范围 — 需在 Epic 模式下处理"
- 向用户展示修订计划供确认
- 生成数据:`$fix_plan`(修订计划)
Step 3:逐项执行修订
- 按修订计划逐项执行文档修改
- 每项修订完成后记录:
- 修改了哪个文件的哪个章节
- 修改前后的关键差异
- 修订是否成功
- 生成数据:`$fix_results`(修订执行结果列表)
Step 4:记录修订总结
- 将修订执行总结整理为结构化内容
- 将总结内容**追加**到最新一轮审查评估文件的 "## 修订执行记录" 章节中
- 如果该章节不存在,在文件末尾创建该章节
- 修订执行记录的开头必须包含元信息:
```
### 修订执行记录
- **Date**: <YYYY-MM-DD>
- **Model Used**: <当前执行本次修订的模型名称>
- **Fix Items**: <修订条目数>
```
- 逐项记录:
```
#### 修订项 #{n}: {问题标题}
- **文件**: {修改的文件路径}
- **章节**: {修改的章节}
- **修改摘要**: {修改前后的关键差异}
- **状态**: {已完成 / 待确认}
```
- 完成后返回:"✅ SR 修订执行完成,修订记录已追加到评估文件"
[注意事项]
- 只修订评估结论中明确标记为"需要修订"的问题,禁止自行扩大修订范围
- 禁止修改任何源码文件
- 修订总结追加到最新一轮(round 值最大)的审查评估文件中
- 路径约定和文件名格式以 references/sr-config.md 为准,不硬编码
- 始终使用中文输出修订记录
- 如果某项修订无法完成(如缺少上下文信息或超出范围),标记为"待确认"并说明原因
- 修订后应重新检查修改内容与 Epic 定义和架构文档的一致性
- 修订执行记录中的 Model Used 字段必须如实填写当前执行修订的模型名称,便于跨 LLM 追溯
- 如果找不到评估文件,立即停止并告知用户
- Story 模式下超出范围的修订项必须明确标记,不得静默跳过
[生成信息] 本 Skill 由 speclite-skill-creator 自动生成。如需修改,建议同步更新 forge/ 和 .claude/skills/ 两份副本,或通过 skills-upgrade 管理版本。
What ships with it
2 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.
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.
- 9d ago First seen · 92 lines · 70 tokens per session scan A b1856f40d307
speclite-story-review-03-fixer is a skill published in the GitHub repository flanliulf/SpecLite (4 stars, last pushed 2mo ago), licensed MIT. It adds 70 tokens to every session and 1,337 once invoked, about $0.0003 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 2026-09-03.
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