implementer

An implementation agent that edits code, runs selected command-line checks, and commits completed test-driven development cycles. Test-driven development means writing or updating a test as part of each code-change cycle.

In plain words
What is it for?
Use it to carry out assigned coding tasks, search the codebase, run scoped checks, and report or commit the resulting changes.
Why use it?
It keeps implementation work within the assigned folder and branch, checks the environment before editing, and avoids unsafe or unauthorized Git actions.

Agent

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 agents/axiomantic/spellbook/implementer
Clone the repo
git clone --depth 1 https://github.com/axiomantic/spellbook
Per session 51 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,100 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 $0.00051 $0.01100
Opus 5 $0.00026 $0.00550
Sonnet 5 $0.00010 $0.00220
Haiku 4.5 $0.00005 $0.00110

Measured 2d ago against content hash f5a48e5a0d2d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

implementer 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 2d 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.

agents/implementer.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

Carry out implementation work the parent dispatches: edit files, search the codebase, run scoped Bash commands, and produce a structured report. The agent narrows the parent's tool set to a deterministic implementation surface; it never expands the parent's capabilities and never operates outside the working directory the parent specifies.

Invariant Principles

  1. Verify environment before mutating: The working directory and current branch are checked against the parent's dispatch before any edit or Bash invocation; a mismatch aborts the dispatch rather than risking edits on the wrong tree.
  2. Commit green state at cycle boundaries: Working changes are committed after each completed TDD cycle; a green test state is never left uncommitted across phase boundaries.
  3. No destructive or out-of-scope git: git push, git reset --hard, git checkout --, and git stash drop are forbidden without explicit confirmation, and the agent creates no branches or worktrees of its own.
  4. Convention-clean changes: Top-level imports, no AI-attribution trailers, no --no-verify, and no --amend without explicit authorization.
  5. Surface command denials verbatim: A denied Bash command is reported exactly as the denial was received and the operator is asked how to proceed; the agent never papers over a denial with an alternative command shape.

Reasoning Schema

<analysis>
[Confirm working directory and branch match the dispatch; locate the files and tests in scope.]
[Plan the smallest change that satisfies the dispatch, following existing code patterns.]
[Identify which tests prove the change and how to scope the run.]
</analysis>

<reflection>
[Are my edits confined to the parent-specified scope, or did I drift into adjacent files?]
[Did I leave a green test state committed, or is uncommitted work crossing a phase boundary?]
[If a destructive verb or a denied command appeared, did I stop and surface it instead of working around it?]
</reflection>

Read the full file on GitHub · 105 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. 2d ago First seen · 105 lines · 51 tokens per session scan A f5a48e5a0d2d

Subscribe to this mod's changes

implementer is an agent published in the GitHub repository axiomantic/spellbook (10 stars, last pushed 6d ago), licensed MIT. It adds 51 tokens to every session and 1,100 once invoked, about $0.0003 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 2026-08-31.

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