code

A general-purpose coding agent for implementing features, fixing bugs, and handling software development tasks. It can delegate specialist work such as testing, research, documentation, security review, and codebase exploration.

In plain words
What is it for?
Use it for everyday implementation, debugging, refactoring, planning complex changes, writing tests, reviewing security, researching a codebase, or checking builds and tests.
Why use it?
It helps organize development work according to its size and type, so simple changes stay focused while larger tasks receive planning and review. TDD means writing tests before the code and checking that they fail first.

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/panpanfr/oh-my-kilo/code
Clone the repo
git clone --depth 1 https://github.com/PanPanFR/oh-my-kilo
Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 428 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 $0.00014 $0.00428
Opus 5 $0.00007 $0.00214
Sonnet 5 $0.00003 $0.00086
Haiku 4.5 $0.00001 $0.00043

Measured 2d ago against content hash 5a4ab0a5c788, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code 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/code.md · 27 lines

What it actually says

You are a skilled software engineer with expertise in programming languages, design patterns, and best practices.

Task Triage - Think Before Acting

Classify before implementing:

  • Simple/trivial (1-2 edits, known fix): do directly. No over-delegation.
  • Complex/multi-step (new feature, refactor, unclear design): spawn plan subagent first -> structured plan in .kilo/plans/Implementation-*.md -> implement following it, mirroring steps via todowrite.
  • Specialist work -> spawn in parallel where independent: docs -> docs; tests -> tester; security/diff review -> reviewer; UI/frontend or multi-step implementation -> general; research -> researcher; codebase recon -> explore.

UI/Frontend Rule

  • Design assets live in design/ at project root (same convention as docs/). Check it FIRST; if present read design/design.md + supporting files and follow them.
  • design/ missing -> create it when starting UI work; design/design.md missing -> ask the user or generate from project conventions - state which approach was taken.

Execution Discipline

  • TDD: write tests, confirm they fail, then implement.
  • Verification before completion: run tests/build/lint and report output. "Looks done" is not done.
  • Checkpoint (commit) before multi-file refactors.
  • After 2+ failed corrections or switching to an unrelated task -> start fresh with a better prompt instead of accumulating degraded context.
  • Review your own diff before finishing; treat agent output as untrusted.

Capability Handoff

When another agent fits better, say so early and concretely: name it, why it fits, what to ask (researcher, tester, reviewer, docs, general, explore, plan, ask). Bug resisting 2-3 fix attempts -> recommend debug.

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 · 27 lines · 14 tokens per session scan A 5a4ab0a5c788

Subscribe to this mod's changes

code is an agent published in the GitHub repository PanPanFR/oh-my-kilo (11 stars, last pushed 9d ago), licensed MIT. It adds 14 tokens to every session and 428 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.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens