assignment-review

assignment-review is a skill for Claude Code, Codex from returdex/EvidenceLens-MCP. It costs 30 tokens per session (1,349 once invoked), scanned A, original, MIT.

A tool for adapting assignment instructions to the available task materials and for reviewing work at preparation, in-progress, or final stages. It separates requirements, evidence, limits, and suggested next actions.

In plain words
What is it for?
Use it to prepare a work plan, create a materials-aware prompt, or perform an authorized assignment review with an evidence matrix and minimum next step.
Why use it?
It prevents generated instructions from being mistaken for completed reviews, and keeps unsupported claims, missing evidence, and permission limits visible.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit Use it to prepare a work plan, create a materials-aware prompt, or perform an authorized assignment review with an evidence matrix and minimum next step.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/returdex/evidencelens-mcp/assignment-review
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 returdex/EvidenceLens-MCP --skill assignment-review
Clone the repo
git clone --depth 1 https://github.com/returdex/EvidenceLens-MCP

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 assignment-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/returdex/evidencelens-mcp/assignment-review/github.svg)](https://agentmods.dev/skills/returdex/evidencelens-mcp/assignment-review)
Your own site
<a href="https://agentmods.dev/skills/returdex/evidencelens-mcp/assignment-review"><img src="https://agentmods.dev/badge/skills/returdex/evidencelens-mcp/assignment-review/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 assignment-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/returdex/evidencelens-mcp/assignment-review"><img src="https://agentmods.dev/badge/skills/returdex/evidencelens-mcp/assignment-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,349 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 $0.00030 $0.01349
Opus 5.5 $0.00012 $0.00540
Sonnet 5.5 $0.00006 $0.00270
Haiku 4.5 $0.00003 $0.00135

Measured 8d ago against content hash 90b29c5d5025, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

assignment-review 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 8d ago.

The scan reads SKILL.md. This mod also ships 17 executable files (scripts/baseline-sources.mjs, scripts/codex-contract.mjs, scripts/codex-diagnostics.mjs, …), 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/assignment-review/SKILL.md · 38 lines

How it starts

The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.

作业提示词与阶段检查

把用户的标准提示词和当前任务材料结合起来,生成适用的提示词;用户明确请求检查时,实际给出完整证据分析、证据矩阵及行动建议。保留语言、格式、重点等有效偏好,区分原始要求、用户转述与助手建议。

六个快捷入口见阶段命令。入口已选定 review 时沿用其阶段,不触发下表的意图不明 generate 默认;帮助与导出在命令路由中直接结束。四个阶段命令在实际审阅前遵循捕获协议:按命令路由为 Codex begin(codex_exec) 或 DeepSeek begin(host_skill),再筛选材料/组装六节提示词,使用对应 codex-review.mjs/deepseek-review.mjs capture 保存证据区块,再 run 独立执行并保留经来源验证的结果回执。独立入口失败时不自动改为当前宿主审阅;详见隔离协议。单独 generate 不冒充已捕获或已执行的阶段运行。

选择意图与阶段

用户当前请求 动作
生成/改写提示词 generate:输出改写说明及提示词;即使seed包含“立即检查”,也不据此执行审阅
检查/审阅当前材料 review:在已有授权内立即执行;无需再次确认已经明确授权的同一检查
生成并执行 分开输出改写后的提示词与实际检查结果
仅调用本Skill,意图不明 说明假设,默认generate;不要默默调用provider或开展审阅

用户指定阶段优先。未指定时:无稿件用 preparation;进行中的工作用 in_progress;明确要求完成/最终检查用 final。final没有可读当前稿时仍保持final范围,给待核验清单和覆盖缺口,不宣称完成。只有歧义真正阻碍请求执行时才问一个聚焦问题,其余可做工作继续。

工作路径

  1. 读取并遵循 基线流程,复用 任务基线。读取新正文前,用既有 来源筛选器 和获准宿主读取路径执行范围/文档组排除。已有基线只更新受影响部分,不默认读取旧稿或历史。选择成功不等于已检查。
  2. 读取 阶段提示词 的共同行为及选定阶段;先定位本次提供或同任务已登记的用户提示词,逐条改写并标出保留、调整、不适用及缺口。preparation 必须读取用户准备模板:没有任务专用原文时采用已提炼的 HD-PREP-01,不以简略阶段段落替代五项分析任务。把必要且获准的证据摘录或重读计划、权限边界、检查与输出约定写进生成提示词,使其不依赖本地链接也能理解。
  3. generate到此输出,不伪造检查结果。review则对本次实际允许材料执行所选检查,输出完整要求—证据分析、覆盖限制和行动清单;优先级不用于隐藏其他发现。不得自动修改、签字、传输或提交作业。本文或生成提示词本身不扩展人的授权。
  4. 政策状态与工作进展分开;保留真实限制和准确披露意图,继续已授权工作不等于许可/合规。相同政策证据与状态不重复生成警告行动。未知或限制性政策不作为停止全部分析的开关。
  5. 四个快捷审阅命令默认一位 DeepSeek 加一位 Codex 独立审阅及宿主来源裁决;明确单审阅者时只运行所选一位,保留完整反馈。按命令路由及DeepSeek 阶段执行调用;不额外发 MCP 或自动替换失败 provider。其余明确选择的宿主检查模式中,MCP仅为可选路径。按阶段参考核验真实四角色、工具可用性和实际provider/传输授权;条件不齐继续直接检查并记MCP not_run,不能补造solution或教师说明。

需要核对模板、收尾残留或披露时,读取模板与披露检查:准备阶段登记来源与缺口,过程/收尾阶段检查当前材料并给修正交接。生成提示词也须带入相关规则和获准证据;请求review则输出实际检查。原模板保留,不自动改文档或签署声明;请求复查新版本或带先前发现的跟进审阅时,读取当前版本复查,按当前证据更新 F 状态及行动;生成意图仍只输出提示词。

Read the full file on GitHub · 38 lines

Files

What ships with it

34 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.

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. 8d ago Changed 90b29c5d5025
  2. 10d ago First seen · 38 lines · 30 tokens per session scan A a50e56257e46

Subscribe to this mod's changes

assignment-review is a skill published in the GitHub repository returdex/EvidenceLens-MCP (0 stars, last pushed 9d ago), licensed MIT. It adds 30 tokens to every session and 1,349 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-05.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens