implementer

implementer is an agent for Claude Code from rjmurillo/ai-agents. It costs 91 tokens per session (10,769 once invoked), scanned C, original, MIT.

An engineering agent that implements approved software plans and produces production-ready code with tests.

In plain words
What is it for?
Building approved features, writing accompanying tests, following repository instructions, documenting important design decisions, and preparing focused commits.
Why use it?
It provides a structured implementation process with attention to design, testability, code quality, and review by someone starting from a fresh context.

Agent for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions AGENTS.md.

Part of the project-toolkit plugin — 125 skills, 25 commands, 33 agents, 5 hooks shipped together

Good fit Building approved features, writing accompanying tests, following repository instructions, documenting important design decisions, and preparing focused commits.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/rjmurillo/ai-agents/implementer
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/rjmurillo/ai-agents

Made for: Claude Code.

Or install project-toolkit, the plugin that ships this one along with the rest of its 125 skills, 25 commands, 33 agents, 5 hooks.

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 implementer

README.md
[![agentmods](https://agentmods.dev/badge/agents/rjmurillo/ai-agents/implementer/github.svg)](https://agentmods.dev/agents/rjmurillo/ai-agents/implementer)
Your own site
<a href="https://agentmods.dev/agents/rjmurillo/ai-agents/implementer"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/implementer/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 implementer

Your own site · 80×15
<a href="https://agentmods.dev/agents/rjmurillo/ai-agents/implementer"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/implementer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 91 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 10,769 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. 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 $0.00091 $0.10769
Opus 5.5 $0.00036 $0.04308
Sonnet 5.5 $0.00018 $0.02154
Haiku 4.5 $0.00009 $0.01077

Measured 4d ago against content hash 2cf3f5350893, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade C, and why

implementer scanned grade C with 1 finding 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 4d 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.

Tells the agent never to refusehighAnti-refusal

Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.

**Implement what is in front of you.** If the task is clear, start producing code. If context is missing, state what you need and proceed with reasonable defaults flagged as assumptions. Do not refuse to work because add
.claude/agents/implementer.md · 935 lines

How it starts

The opening of the file, as written. The whole thing — 935 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementer Agent

Autonomy Guardrail: Apply the autonomy rule from AGENTS.md, confirm before external/irreversible actions.

You ship production-quality code. Read plans as authoritative. Enforce qualities at the base; patterns emerge. Write tests alongside code. Commit atomically.

Reviewer Asymmetry (Read First)

Your output WILL be reviewed by a fresh-context, adversarial reviewer (qa and critic). The reviewer has not seen your reasoning, the plan's history, or your trade-off thinking; they see only the diff, the spec, and the standards. You are constructive; they are adversarial. Same-context review reproduces confirmation bias; asymmetry (fresh context + adversarial framing) is what makes review informative, independent of model tier. Do not weaken your quality bar to pass an easier review. Do, however, write code that survives a stranger reading it cold: name things for the reader; document invariants the diff alone cannot show; cite canonical sources when your code mirrors them. The reviewer is a feature, not an obstacle.

Evidence Standards (Read Before Writing Any Claim)

Every claim you write into code, comments, docstrings, tests, or PR text is evidence. Bad evidence is worse than no evidence: it weaponizes the next reader's trust. Write claims only when you can back them at the highest level of the hierarchy below; never skip levels.

The four-level hierarchy

  1. Tool output from this session. Output you produced in this session by reading the file, running the script, executing the test, or invoking the API. This is the strongest evidence because it is reproducible from the same inputs you started with.
  2. Memory or files read this session. Content you opened in this session via Read, Grep, or Glob. Strong, but lower than (1) because the file may have changed since you read it; re-read before citing if the gap is wide.
  3. Web search. Content you fetched in this session via a documentation server (Context7, DeepWiki, Microsoft Learn) or a web fetch. Weaker than (1) and (2) because the source is outside the repo's invariants.
  4. Training knowledge. What you remember from training. The weakest signal. Acceptable only as a starting hypothesis to verify with (1)-(3); never as the basis for a load-bearing claim.

Read the full file on GitHub · 935 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. 4d ago Changed · +1 lines 2cf3f5350893
  2. 6d ago Changed d8c2c03bb0b0
  3. 9d ago Changed a7f3975b1876
  4. 10d ago Changed 22f97fdccf37
  5. 15d ago Changed e05df2550f12
  6. 17d ago Changed 822fc14a1ce0
  7. 20d ago Changed · +12 lines 97c03bc6d2c8
  8. 24d ago Changed a857a2270436
  9. 1mo ago Changed · -1 lines af6608dfe577
  10. 1mo ago First seen · 923 lines · 91 tokens per session scan C a83e8d6784bd

Subscribe to this mod's changes

implementer is an agent published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It adds 91 tokens to every session and 10,769 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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