speckit.analyze

speckit.analyze is an agent for Claude Code from jamalla/mcp-gateway-worker. It costs 26 tokens per session (1,518 once invoked), scanned A, original, no licence file.

An agent that checks specification, plan, and task files for consistency and quality after tasks have been generated.

In plain words
What is it for?
It is for reviewing spec.md, plan.md, and tasks.md together after task generation.
Why use it?
It can reveal mismatches or quality problems across these project documents without changing them.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

Good fit It is for reviewing spec.md, plan.md, and tasks.md together after task generation.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/jamalla/mcp-gateway-worker/speckit.analyze
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.

Clone the repo
git clone --depth 1 https://github.com/jamalla/mcp-gateway-worker

Made for: Claude Code.

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 speckit.analyze

README.md
[![agentmods](https://agentmods.dev/badge/agents/jamalla/mcp-gateway-worker/speckit.analyze.svg)](https://agentmods.dev/agents/jamalla/mcp-gateway-worker/speckit.analyze)
Your own site
<a href="https://agentmods.dev/agents/jamalla/mcp-gateway-worker/speckit.analyze"><img src="https://agentmods.dev/badge/agents/jamalla/mcp-gateway-worker/speckit.analyze.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,518 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 unknown 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 $0.01518
Opus 5 $0.00013 $0.00759
Sonnet 5 $0.00005 $0.00304
Haiku 4.5 $0.00003 $0.00152

Measured 6d ago against content hash e1f7958c4a6b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

speckit.analyze 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.

.github/agents/speckit.analyze.agent.md · 185 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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 · 185 lines · 26 tokens per session scan A e1f7958c4a6b

Subscribe to this mod's changes

speckit.analyze is an agent published in the GitHub repository jamalla/mcp-gateway-worker (0 stars, last pushed 6mo ago), with no licence file. It adds 26 tokens to every session and 1,518 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 2026-09-01.

Related

Other agents, from other repositories

context-promoter

Reviews unpromoted journal entries and helps the owner promote them into curated context. Use when the owner says "promote journal", "review my journal", "update my context memory", or runs the promotion workflow. Read-and-suggest only: this agent NEVER writes curated files itself.

dkritarth/context-kernel · 61 tokens

effect-ts-enforcer

Reviews a diff or file set against the 5 non-negotiables (Effect TS default, no Zod, tagged errors mapped in tagToTRPC, no process.env, unit test for every helper/repo). One line per violation, severity-tagged, no praise. Use AFTER writing code and BEFORE /verify-done. Examples — "review my changes to…

SeanningTatum/cf-saas-starter-react-router · 110 tokens

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens