What is feature-report?

A command that creates a report comparing a completed feature with its product requirements, design, and optional quality-assurance test plan. A PRD is a document describing what a product should do, while Figma is a design tool and Confluence is a shared documentation service.

Use it after implementation to review a feature against a Confluence PRD, Figma designs, the codebase, and, when provided, QA test scenarios.

It helps reveal where the implementation differs from the agreed requirements or visual design instead of relying only on task tickets.

How tomdwipo/claude-soul configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to tomdwipo/claude-soul. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/tomdwipo/claude-soul/main/.claude/commands/feature-report.md

Clone the repo

git clone --depth 1 https://github.com/tomdwipo/claude-soul

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/commands/tomdwipo/claude-soul/feature-report/github.svg)](https://agentmods.dev/commands/tomdwipo/claude-soul/feature-report)

Your own site

<a href="https://agentmods.dev/commands/tomdwipo/claude-soul/feature-report"><img src="https://agentmods.dev/badge/commands/tomdwipo/claude-soul/feature-report/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/commands/tomdwipo/claude-soul/feature-report"><img src="https://agentmods.dev/badge/commands/tomdwipo/claude-soul/feature-report.svg" alt="Reviewed on agentmods" width="80" 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 2,019 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 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 5.1	$0.00000	$0.02019
Opus 5.5	$0.00000	$0.00808
Sonnet 5.5	$0.00000	$0.00404
Haiku 4.5	$0.00000	$0.00202

Measured 2mo ago against content hash 3c7ccb76a1a8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

feature-report 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 2mo 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.

.claude/commands/feature-report.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Feature Report Command (Phase 2: Post-Implementation)

Generate a compliance feature report for: $ARGUMENTS

Instructions

Step 1: Gather PRD & Design Inputs

Primary inputs for feature reports are PRD (Confluence), Figma design, and actual implemented codebase — NOT Jira tickets.

1a. PRD from Confluence (Primary Source of Truth)

If $ARGUMENTS contains a Confluence URL or page ID:

Use mcp__atlassian__getConfluencePage to fetch PRD content
Extract: requirements, acceptance criteria, business rules — this is what implementation is compared against

If $ARGUMENTS describes a feature name (no URL):

Use mcp__atlassian__searchConfluenceUsingCql to search for the PRD in Confluence
Fetch the matching page with mcp__atlassian__getConfluencePage

1b. Figma Design

If $ARGUMENTS contains a Figma URL:

Use mcp__figma__get_file_nodes to fetch design details

If user provides screenshot images directly:

Analyze the screenshots for UI compliance verification

1c. QA TRD

If $ARGUMENTS contains --qa-trd or a QA TRD Confluence URL:

Fetch QA TRD from Confluence to enrich QA_ALIGNMENT.md
Map QA test scenarios against implementation

1d. Jira (Optional — for ticketing/tracking only)

If $ARGUMENTS contains a Jira ticket ID (e.g., PROJ-1234):

Use mcp__atlassian__getJiraIssue to fetch ticket summary, epic, linked issues
Use mcp__jira-attachment__list_attachments + download_all_images + download_all_videos for attachments
If videos found, use mcp__video-to-image__extract_frames_by_count (count: 5) to extract key frames
Note: Jira is used for tracking context and ticket references only, not as primary requirement source

Step 2: Analyze Implemented Code

Read the existing TRD at .docs/trd/TRD-{Feature-Name}.md if it exists
Search codebase for all files mentioned in the TRD or related to the feature
Read actual implemented files to verify what was built
Compare implementation against PRD requirements from Confluence
Identify any gaps or deviations from the original spec

Read the full file on GitHub · 296 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.

2mo ago First seen · 296 lines · 0 tokens per session scan A 3c7ccb76a1a8

Subscribe to this mod's changes

feature-report is a command published in the GitHub repository tomdwipo/claude-soul (24 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,019 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 2026-08-30.

Planning

feature-report next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
feature-reporttomdwipo/claude-soul	Command	24	2mo ago	MIT	A	0	Claude Code
checklistgithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
clarifygithub/spec-kit	Command	148k	yesterday	MIT	A	27	Claude Code
specifygithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
analyzegithub/spec-kit	Command	148k	yesterday	MIT	A	26	Claude Code
convergegithub/spec-kit	Command	148k	yesterday	MIT	A	35	Claude Code
implementgithub/spec-kit	Command	148k	yesterday	MIT	A	14	Claude Code

claude-soul: Command for Claude Code