What is gtd-doc-classifier?

A document classifier that labels one planning document as an ADR, PRD, SPEC, DOC, or UNKNOWN. It also extracts the title, a scope summary, and links to related documents, then saves the result as JSON.

Sorting architecture decisions, product requirements, technical specifications, and general documentation during document ingestion. ADR means a record of a technical decision; PRD means a description of what a product or feature should do.

It prevents important documents from being placed in the wrong category. That helps later steps extract requirements and preserve architectural decisions correctly.

gtd-doc-classifier — Agent for Claude Code by ai-is-gonna

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/ai-is-gonna/get-tasks-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.

README.md

[![agentmods](https://agentmods.dev/badge/agents/ai-is-gonna/get-tasks-done/gtd-doc-classifier/github.svg)](https://agentmods.dev/agents/ai-is-gonna/get-tasks-done/gtd-doc-classifier)

Your own site

<a href="https://agentmods.dev/agents/ai-is-gonna/get-tasks-done/gtd-doc-classifier"><img src="https://agentmods.dev/badge/agents/ai-is-gonna/get-tasks-done/gtd-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.

Your own site · 80×15

<a href="https://agentmods.dev/agents/ai-is-gonna/get-tasks-done/gtd-doc-classifier"><img src="https://agentmods.dev/badge/agents/ai-is-gonna/get-tasks-done/gtd-doc-classifier.svg" alt="Reviewed on agentmods" width="80" 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. A grade says what 26 rules found in the file — not that it is safe.

Origin 95% 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.

Model	Per session	Once 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 10d ago against content hash a3fdf3475e37, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

gtd-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 10d 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

95% identical to gsd-doc-classifier — 6 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.

agents/gtd-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.

10d ago First seen · 169 lines · 63 tokens per session scan A a3fdf3475e37

Subscribe to this mod's changes

gtd-doc-classifier is an agent published in the GitHub repository ai-is-gonna/get-tasks-done (9 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. It is 95% identical to gsd-doc-classifier, differing in 6 lines, and is treated as a copy.

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