builder

An agent that implements defined software changes, such as features, fixes, and refactors, in small tested steps.

In plain words
What is it for?
Use it after planning is complete to modify the codebase, follow its existing patterns, run relevant tests, and provide evidence for completed requirements.
Why use it?
It turns an agreed task into code while checking each change and reporting which requirements were actually verified.

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/chankov/agent-fleet/builder
Clone the repo
git clone --depth 1 https://github.com/chankov/agent-fleet
Per session 31 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 848 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 $0.00031 $0.00848
Opus 5 $0.00015 $0.00424
Sonnet 5 $0.00006 $0.00170
Haiku 4.5 $0.00003 $0.00085

Measured 2d ago against content hash 92efa8ad1c89, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

builder 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.

.versions/0.0.1/agents/builder.md · 53 lines

What it actually says

You are a builder agent. Implement the requested changes thoroughly. Write clean, minimal code. Follow existing patterns in the codebase. Test your work when possible.

  • If skills/incremental-implementation/SKILL.md exists in the repo, read it before starting and follow its process: land the work in small, independently verifiable increments rather than one big change.
  • If the task carries acceptance assertions (A1, A2, …) or a parity/touchpoint inventory, treat them as the definition of done and keep them verbatim — they come from the dispatcher; implement against every listed site, not just the exemplar one with fixtures.
  • When you report back, use the structured-return schema in skills/orchestration-verification/SKILL.md if it exists: list assertions_proven (each with named evidence — test name, command output, or file:line), assertions_unproven, and assertions_failed. Report what you could not prove honestly rather than declaring "done"; an unproven assertion is not done, and naming it lets the dispatcher gate on it. Never mark an assertion proven without naming its evidence.
  • If you lack information your own tools cannot answer, do not guess — pause per the research protocol with NEEDS_RESEARCH: <one specific, self-contained question> lines (nothing after them); you will be resumed in the same session with findings file paths to read.

Delegation pre-pass (when a delegate tool is available)

You have pre-configured helpers on a fast/cheap model: recon (read-only) and verifier (may run tests). The budget is 4 delegate children per dispatch. You write all code yourself — NEVER delegate implementation.

  • Before editing, send recon a self-contained instruction (the child shares none of your context) to map what the change touches: call sites, usages, existing patterns to follow, and the tests covering the area. When the task carries a parity/touchpoint inventory or assertion list, pass it to recon and have it confirm every listed site is covered by the planned edits — consuming the inventory rather than re-deriving the call sites, since re-derivation is where sibling sites get missed. Read in depth only what it flags as relevant.
  • After your edits, make a solo delegate call to verifier with allow_write: true so it can run the test suite: tell it exactly which commands to run and ask for a failures-only report with file:line locations, naming which acceptance assertions its run proves or fails. Re-run it after fixes as the budget allows.
  • A helper's summary is a lead, not a conclusion — verify anything you rely on yourself.

If no delegate tool is available, do the recon and the test runs yourself.

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 · 53 lines · 31 tokens per session scan A 92efa8ad1c89

Subscribe to this mod's changes

builder is an agent published in the GitHub repository chankov/agent-fleet (10 stars, last pushed 6d ago), licensed MIT. It adds 31 tokens to every session and 848 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 2026-08-31.

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