What is code-annotate?

A helper for adding an `implements` comment to a function, linking that function to an existing requirement or design record.

Use it when writing implementation code to insert the reference in the correct place and verify that the annotation can be read by project checks.

It reduces manual annotation work and checks that the referenced record exists and the comment uses the right syntax for the programming language.

code-annotate — Skill for Claude Code and Codex by SteveGJones: A helper for adding an implements comment to a…

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 skills/stevegjones/ai-first-sdlc-practices/code-annotate

Any agent

npx skills add SteveGJones/ai-first-sdlc-practices --skill code-annotate

Clone the repo

git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practices

Made for: Claude Code, Codex.

Or install sdlc-assured, the plugin that ships this one along with the rest of its 8 skills.

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/skills/stevegjones/ai-first-sdlc-practices/code-annotate.svg)](https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/code-annotate)

Your own site

<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/code-annotate"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/code-annotate.svg" alt="Measured on agentmods" height="20"></a>

Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 520 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.

Model	Per session	Once invoked
Fable 5	$0.00034	$0.00520
Opus 5	$0.00017	$0.00260
Sonnet 5	$0.00007	$0.00104
Haiku 4.5	$0.00003	$0.00052

Measured 3d ago against content hash f780f28d241e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-annotate 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 3d 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.

plugins/sdlc-assured/skills/code-annotate/SKILL.md · 52 lines

How it starts

The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: code-annotate

Use this skill when adding implementation code that satisfies a REQ or DES. Generates the correct # implements: annotation, validates that the cited IDs exist in the registry, and inserts the annotation in a syntactically-correct place.

Inputs

<artefact-id> — the REQ or DES being implemented (e.g., REQ-auth-001, DES-auth-001, or P1.SP2.M3.REQ-007)
File path and function name (from active editing context)

Steps

Verify the artefact exists. Read library/_ids.md; confirm <artefact-id> is declared.
Detect the language. Python (#), JavaScript/TypeScript (//), Go (//), Rust (//). Default # if unknown.
Determine the comment line. Choose the comment syntax matching the file extension.
Insert the annotation. Place <comment-prefix> implements: <artefact-id> as the first line of the function body, immediately after the opening brace / : / func ... {.
Confirm. Show the diff to the user.
Run annotation_format_integrity on the file to verify the annotation parses correctly.

Annotation placement rules

 and # implements: <DES-ID> annotations ALWAYS go on the implementing artefact:

A Python function body — first line of the body, comment form
A SKILL.md file — immediately after frontmatter close ---, HTML-comment form
A governance document — YAML frontmatter satisfies_by_existence: [...] or implements: [...]

NEVER place annotations:

Inside a design-spec.md DES element (the DES is what is satisfied, not what implements)
Inside a requirements-spec.md REQ element
Inside a test-spec.md TEST element

The spec layer expresses obligation; the implementing artefact carries evidence. Crossing the layers blurs the audit trail.

Done criteria

Annotation inserted in syntactically-correct location.
annotation_format_integrity passes.
One commit with the annotation; the implementing code is the user's responsibility.

Read the full file on GitHub · 52 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.

3d ago First seen · 52 lines · 34 tokens per session scan A f780f28d241e

Subscribe to this mod's changes

code-annotate is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 25d ago), licensed MIT. It adds 34 tokens to every session and 520 once invoked, about $0.0002 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.

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