agentmods.dev

review-needs-assessment

review-needs-assessment is a skill for Claude Code, Codex from tomzx/agents. It costs 26 tokens per session (1,033 once invoked), scanned A, original, MIT.

A review of a needs assessment, which explains who has a problem, what evidence supports it, and whether the problem should be addressed. It checks the evidence, affected groups, alternatives, and final recommendation.

In plain words
What is it for?
Evaluating problem statements, user or stakeholder research, alternative solutions, and the decision to proceed.
Why use it?
It helps prevent teams from committing to work based on weak evidence, incomplete stakeholder input, or an unsupported conclusion.

Skill for Claude CodeCodex

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

not rated 6repo yesterday A scan 26 tokens original MIT

Good fit Evaluating problem statements, user or stakeholder research, alternative solutions, and the decision to proceed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tomzx/agents/review-needs-assessment
View source ↗ tomzx/agents
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 tomzx/agents --skill review-needs-assessment
Clone the repo
git clone --depth 1 https://github.com/tomzx/agents

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 review-needs-assessment

README.md
[![agentmods](https://agentmods.dev/badge/skills/tomzx/agents/review-needs-assessment/github.svg)](https://agentmods.dev/skills/tomzx/agents/review-needs-assessment)
Your own site
<a href="https://agentmods.dev/skills/tomzx/agents/review-needs-assessment"><img src="https://agentmods.dev/badge/skills/tomzx/agents/review-needs-assessment/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 review-needs-assessment

Your own site · 80×15
<a href="https://agentmods.dev/skills/tomzx/agents/review-needs-assessment"><img src="https://agentmods.dev/badge/skills/tomzx/agents/review-needs-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,033 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 $0.00026 $0.01033
Opus 5 $0.00013 $0.00517
Sonnet 5 $0.00005 $0.00207
Haiku 4.5 $0.00003 $0.00103

Measured 6d ago against content hash b47830b913d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

review-needs-assessment 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 6d 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.

skills/review-needs-assessment/SKILL.md · 103 lines

How it starts

The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Needs Assessment

Audits a needs assessment and reports findings across four categories: evidence rigor, stakeholder coverage, alternative-path completeness, and verdict soundness.

Prerequisites

  • Apply the shared SDLC conventions in skills/sdlc/references/shared.md.
  • If no argument is provided, locate the feature directory under .sdlc/features/ whose frontmatter issue field references $ISSUE_NUMBER.
  • .sdlc/features/N-<slug>/needs-assessment.md, or a needs assessment document provided in context or as a file path

Steps

  1. Read the needs assessment document from .sdlc/features/N-<slug>/needs-assessment.md if present, otherwise from context or as a file path.
  2. Identify issues in each of the four categories below.
  3. Report findings using the output format. Omit any category that has no findings.
  4. Write the findings to .sdlc/features/N-<slug>/review-needs-assessment.md with frontmatter artifact: needs-assessment, verdict (approved if the overall verdict is Needed or Nice-to-have, rejected if Not needed, changes-requested if the author must address findings), and reviewed_at: <ISO date>, and the findings as the body, per skills/sdlc/references/shared.md. Record any unresolved open questions in the findings body.
    • If the overall verdict is Not needed: also update the GitHub issue with the findings and stop the pipeline.

Review Checklist

Evidence Rigor

  • Is the problem stated as a problem (not a solution)?
  • Is evidence drawn from concrete sources (tickets, data, feedback) or is it purely assumed?
  • If evidence is Weak or None, is this explicitly flagged as an open question?
  • Are there evidence sources that were not checked but should have been (support logs, analytics, user interviews)?

Stakeholder Coverage

  • Are all affected stakeholder groups identified, not just the most vocal?
  • Is it clear who benefits and who is inconvenienced by the current state?
  • Are edge-case stakeholders (admin, internal tools, accessibility) considered?

Read the full file on GitHub · 103 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. 6d ago First seen · 103 lines · 26 tokens per session scan A b47830b913d7

Subscribe to this mod's changes

review-needs-assessment is a skill published in the GitHub repository tomzx/agents (6 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 1,033 once invoked, about $0.0001 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.

PlanningResearch
Related

Other skills, from other repositories

systematic-debugging

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

obra/superpowers · 21 tokens

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

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

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

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens