implement-feature

implement-feature is a command for Claude Code from saeedkolivand/ai-job-hunter-app. It costs 22 tokens per session (351 once invoked), scanned A, original, Apache-2.0.

An end-to-end feature implementation command that follows a review process, assigns a primary owner, may add tests, and keeps documentation in sync.

In plain words
What is it for?
Use it to build a feature from code changes through review, conditional testing, and documentation updates.
Why use it?
It organizes the work needed to deliver a feature while making review, testing, and documentation part of the same process.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Good fit Use it to build a feature from code changes through review, conditional testing, and documentation updates.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/saeedkolivand/ai-job-hunter-app/implement-feature
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/saeedkolivand/ai-job-hunter-app

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 implement-feature

README.md
[![agentmods](https://agentmods.dev/badge/commands/saeedkolivand/ai-job-hunter-app/implement-feature/github.svg)](https://agentmods.dev/commands/saeedkolivand/ai-job-hunter-app/implement-feature)
Your own site
<a href="https://agentmods.dev/commands/saeedkolivand/ai-job-hunter-app/implement-feature"><img src="https://agentmods.dev/badge/commands/saeedkolivand/ai-job-hunter-app/implement-feature/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.

agentmods 80×15 button for implement-feature

Your own site · 80×15
<a href="https://agentmods.dev/commands/saeedkolivand/ai-job-hunter-app/implement-feature"><img src="https://agentmods.dev/badge/commands/saeedkolivand/ai-job-hunter-app/implement-feature.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 351 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.00351
Opus 5 $0.00011 $0.00176
Sonnet 5 $0.00004 $0.00070
Haiku 4.5 $0.00002 $0.00035

Measured 9d ago against content hash 395ef0bb9303, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

implement-feature 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 9d 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/implement-feature.md · 19 lines

What it actually says

Implement: $ARGUMENTS

Follow the review-workflow skill exactly:

  1. Load review-workflow + token-efficiency + coding-standards.
  2. Analyze — graphify/codegraph-scope affected files; identify the area's author + critic pair (Ownership precedence). Pre-harvest into .claude/scratch/<task>.md. Stop at ~90% confidence.
  3. Plan the minimal change (Rust-first for business logic; new IPC capability → the 5-file flow in tauri-standards).
  4. Implement — the domain author (loads author-contract) makes minimal changes on a feature branch (PRs only — never push to main); appends what changed to the handoff.
  5. Test stage (if touchesTestableLogic): test-author writes tests → testing-reviewer audits coverage of the changed code.
  6. Review — the independent critic (never the author) audits (+ Secondary only on risk, ≤3 critics); HIGH/CRITICAL block → author resolves → re-audit.
  7. Verify correctness (pnpm test / cargo test), performance & security where applicable.
  8. Docs + lessonsproject-steward syncs affected docs/knowledge, runs graphify update ., persists any durable lesson.
  9. Open a PR (gh pr create) and wait for approval.
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. 9d ago First seen · 19 lines · 22 tokens per session scan A 395ef0bb9303

Subscribe to this mod's changes

implement-feature is a command published in the GitHub repository saeedkolivand/ai-job-hunter-app (54 stars, last pushed today), licensed Apache-2.0. It adds 22 tokens to every session and 351 once invoked, about $0.0001 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.