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sdlc-intake

sdlc-intake is a command for coding agents from MCKRUZ/claude-code-sdlc. It costs 0 tokens per session (957 once invoked), scanned A, original, MIT.

A command that turns external project documents—such as requests for proposals, API descriptions, supplier information, and presentation decks—into an organized set of summaries.

In plain words
What is it for?
Use it to collect document metadata, estimate token counts, and create reusable summaries for a software project or client engagement.
Why use it?
It removes the need to catalog documents manually or run the underlying script yourself. It also prepares summaries sized for an AI agent's context limits.

Command

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the claude-code-sdlc plugin — 9 skills, 28 commands, 20 agents shipped together

not rated 4 7d ago A scan 0 tokens original MIT
View the source file MCKRUZ/claude-code-sdlc
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 commands/mckruz/claude-code-sdlc/sdlc-intake
Clone the repo
git clone --depth 1 https://github.com/MCKRUZ/claude-code-sdlc

Or install claude-code-sdlc, the plugin that ships this one along with the rest of its 9 skills, 28 commands, 20 agents.

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 sdlc-intake

README.md
[![agentmods](https://agentmods.dev/badge/commands/mckruz/claude-code-sdlc/sdlc-intake.svg)](https://agentmods.dev/commands/mckruz/claude-code-sdlc/sdlc-intake)
Your own site
<a href="https://agentmods.dev/commands/mckruz/claude-code-sdlc/sdlc-intake"><img src="https://agentmods.dev/badge/commands/mckruz/claude-code-sdlc/sdlc-intake.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 957 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 $0.00000 $0.00957
Opus 5 $0.00000 $0.00478
Sonnet 5 $0.00000 $0.00191
Haiku 4.5 $0.00000 $0.00096

Measured 5d ago against content hash c0570045a4dc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sdlc-intake 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 5d 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.

commands/sdlc-intake.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/sdlc-intake — Catalog and Summarize the Document Corpus

Process external reference documents (RFPs, API specs, vendor docs, decks) into a cataloged, token-budgeted set of summaries for use across the engagement. This is the Phase 0 Step 0c workflow wrapped as one command, so no one runs the cataloger script by hand.

Instructions

  1. Locate state file: Look for .sdlc/state.yaml in the current project directory. If not found, tell the user to run /sdlc-setup first.

  2. Resolve the intake source:

    • Workflow mode (default): read the documentation.intake_path from .sdlc/profile.yaml. If the profile has no documentation section, tell the user document intake is not configured for this profile and stop (or offer to add it).
    • --docs <path>: use the given folder instead of the profile path (standalone use).

  3. Run the cataloger: Execute the intake script — the user never calls it directly:

    uv run --project ${CLAUDE_PLUGIN_ROOT}/scripts ${CLAUDE_PLUGIN_ROOT}/scripts/intake_documents.py --state .sdlc/state.yaml

    This produces .sdlc/context/intake/catalog.json with document metadata (DOC-NNN IDs, types, token estimates, checksums). Pass --rescan through when the user runs /sdlc-intake --rescan.

  4. Review the catalog with the human:

HITL GATE: Present the catalog using the AskUserQuestion tool: "I found N documents in [intake_path] totaling ~X estimated tokens: [table of DOC-NNN | filename | type | est. tokens]. (1) Are all relevant documents present, or should any be added/removed? (2) Which are highest priority for understanding the project? (3) Any to skip?" Adjust before proceeding.

  1. Generate per-document summaries: For each document (respecting max_documents), ordered by human-indicated priority: read the content, write a summary following the document-summary.md template to .sdlc/context/intake/DOC-NNN-{slug}.md, targeting summary_budget_tokens. For any document over ~100K tokens, chunk it (first and last 10% plus section headers) and flag the summary as a partial extraction.

Read the full file on GitHub · 74 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. 5d ago First seen · 74 lines · 0 tokens per session scan A c0570045a4dc

Subscribe to this mod's changes

sdlc-intake is a command published in the GitHub repository MCKRUZ/claude-code-sdlc (4 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 957 tokens. 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 2026-08-31.

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