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gsd-doc-classifier

gsd-doc-classifier is an agent for Claude Code from gsd-build/get-shit-done. It costs 63 tokens per session (1,876 once invoked), scanned A, original, MIT.

A document sorter for planning files. It labels one file as an architecture decision, product requirements, technical specification, general documentation, or unknown, then records its title, summary, and links to related files.

In plain words
What is it for?
Use it when importing project documents into a planning workflow. It creates a JSON classification file for each document and confirms the result.
Why use it?
It prevents planning information from being placed in the wrong category, where requirements or technical decisions could be missed or given the wrong priority.

Agent for Claude Code

Written for Claude Code: PostToolUse hook event.

not rated 65k +8 3mo ago A scan 63 tokens original MIT archived
View the source file gsd-build/get-shit-done
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.

agentmods
npx agentmods add agents/gsd-build/get-shit-done/gsd-doc-classifier
Clone the repo
git clone --depth 1 https://github.com/gsd-build/get-shit-done

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/gsd-build/get-shit-done/gsd-doc-classifier.svg)](https://agentmods.dev/agents/gsd-build/get-shit-done/gsd-doc-classifier)
Your own site
<a href="https://agentmods.dev/agents/gsd-build/get-shit-done/gsd-doc-classifier"><img src="https://agentmods.dev/badge/agents/gsd-build/get-shit-done/gsd-doc-classifier.svg" alt="Measured on agentmods" height="20"></a>
Per session 63 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,876 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00063 $0.01876
Opus 5 $0.00032 $0.00938
Sonnet 5 $0.00013 $0.00375
Haiku 4.5 $0.00006 $0.00188

Measured 6d ago against content hash b624f1608f56, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, 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 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.

Origin

Copies of this mod

8 near-identical copies found in the catalogue:

agents/gsd-doc-classifier.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 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.

<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-*.md…9999-*.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.

Confidence:

  • high — frontmatter or filename convention + matching content signals
  • medium — content signals only, one dominant
  • low — signals conflict or are thin → classify as best guess but flag the low confidence

Read the full file on GitHub · 169 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 · 169 lines · 63 tokens per session scan A b624f1608f56

Subscribe to this mod's changes

gsd-doc-classifier is an agent published in the GitHub repository gsd-build/get-shit-done (64,600 stars, last pushed 3mo ago), licensed MIT. It adds 63 tokens to every session and 1,876 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 2026-08-30.

Documentsclaude-codecontext-engineeringmeta-promptingspec-driven-development
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