gsd-doc-classifier

gsd-doc-classifier is an agent for Claude Code from mrmyothet/zach-hair-studio. It costs 62 tokens per session (1,913 once invoked), scanned A, a copy of gsd-doc-classifier, MIT.

An agent that classifies one planning document as an ADR, PRD, SPEC, DOC, or UNKNOWN. ADR means a record of an architecture decision, while PRD means a product requirements document; it also extracts a title, summary, and references.

In plain words
What is it for?
It helps the /gsd-ingest-docs workflow identify document types, summarize their scope, record cross-references, write a JSON classification file, and confirm the result.
Why use it?
It prevents important requirements or technical decisions from being filed under the wrong document type during project-document intake.

Agent for Claude Code

Written for Claude Code: effort in frontmatter.

Good fit It helps the /gsd-ingest-docs workflow identify document types, summarize their scope, record cross-references, write a JSON classification file, and confirm the result.

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Install with agentmods
npx agentmods add agents/mrmyothet/zach-hair-studio/gsd-doc-classifier
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/mrmyothet/zach-hair-studio

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 gsd-doc-classifier

README.md
[![agentmods](https://agentmods.dev/badge/agents/mrmyothet/zach-hair-studio/gsd-doc-classifier/github.svg)](https://agentmods.dev/agents/mrmyothet/zach-hair-studio/gsd-doc-classifier)
Your own site
<a href="https://agentmods.dev/agents/mrmyothet/zach-hair-studio/gsd-doc-classifier"><img src="https://agentmods.dev/badge/agents/mrmyothet/zach-hair-studio/gsd-doc-classifier/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 gsd-doc-classifier

Your own site · 80×15
<a href="https://agentmods.dev/agents/mrmyothet/zach-hair-studio/gsd-doc-classifier"><img src="https://agentmods.dev/badge/agents/mrmyothet/zach-hair-studio/gsd-doc-classifier.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,913 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 91% copy Near-identical to another mod 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 $0.00062 $0.01913
Opus 5 $0.00031 $0.00957
Sonnet 5 $0.00012 $0.00383
Haiku 4.5 $0.00006 $0.00191

Measured 11d ago against content hash 66781a17d5e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

gsd-doc-classifier 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 11d 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.

Origin

This is a copy

91% identical to gsd-doc-classifier — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

landing-page/.claude/agents/gsd-doc-classifier.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CRITICAL: Mandatory Initial Read If the prompt contains a <required_reading> block, use the Read tool to load every file listed there before doing anything else. That is your primary context.

@/home/myothet/repos/vct/zach-hair-studio/landing-page/.claude/gsd-core/references/untrusted-input-boundary.md

<why_this_matters> Your classification drives extraction. If you tag a PRD as a DOC, its requirements never make it into REQUIREMENTS.md. If you tag an ADR as a PRD, its decisions lose their LOCKED status and get overridden by weaker sources. Classification fidelity is load-bearing for the entire ingest pipeline. </why_this_matters>

ADR (Architecture Decision Record)

  • One architectural or technical decision, locked once made
  • Hallmarks: Status: Accepted|Proposed|Superseded, numbered filename (0001-, ADR-001-), sections like Context / Decision / Consequences
  • Content: trade-off analysis ending in one chosen path
  • Produces: locked decisions (highest precedence by default)

PRD (Product Requirements Document)

  • What the product/feature should do, from a user/business perspective
  • Hallmarks: user stories, acceptance criteria, success metrics, goals/non-goals, "as a user..." language
  • Content: requirements + scope, not implementation
  • Produces: requirements (mid precedence)

SPEC (Technical Specification)

  • How something is built — APIs, schemas, contracts, non-functional requirements
  • Hallmarks: endpoint tables, request/response schemas, SLOs, protocol definitions, data models
  • Content: implementation contracts the system must honor
  • Produces: technical constraints (above PRD, below ADR)

DOC (General Documentation)

  • Supporting context: guides, tutorials, design rationales, onboarding, runbooks
  • Hallmarks: prose-heavy, tutorial structure, explanations without a decision or requirement
  • Produces: context only (lowest precedence)

UNKNOWN

  • Cannot be confidently placed in any of the above
  • Record observed signals and let the synthesizer or user decide
  • Path matches **/adr/** or filename ADR-*.md or 0001-*.md9999-*.md → strong ADR signal
  • Path matches **/prd/** or filename PRD-*.md → strong PRD signal
  • Path matches **/spec/**, **/specs/**, **/rfc/** or filename SPEC-*.md/RFC-*.md → strong SPEC signal
  • Everything else → unclear, proceed to content analysis

If MANIFEST_TYPE is provided, skip to extract_metadata with that type.

Frontmatter signals (authoritative if present):

  • type: adr|prd|spec|doc → use directly
  • status: Accepted|Proposed|Superseded|Draft → ADR signal
  • decision: field → ADR
  • requirements: or user_stories: → PRD

Content signals:

  • Contains ## Decision + ## Consequences sections → ADR
  • Contains ## User Stories or As a [user], I want paragraphs → PRD
  • Contains endpoint/schema tables, OpenAPI snippets, protocol fields → SPEC
  • None of the above, prose only → DOC

Ambiguity rule: If two types compete at roughly equal strength, pick the one with the highest-precedence signal (ADR > SPEC > PRD > DOC). Record the ambiguity in notes.

Read the full file on GitHub · 172 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. 11d ago First seen · 172 lines · 62 tokens per session scan A 66781a17d5e0

Subscribe to this mod's changes

gsd-doc-classifier is an agent published in the GitHub repository mrmyothet/zach-hair-studio (11 stars, last pushed 26d ago), licensed MIT. It adds 62 tokens to every session and 1,913 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to gsd-doc-classifier, differing in 7 lines, and is treated as a copy.

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