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.
npx agentmods add skills/vodailocz/kilo-kit-mcp/code-agent-patternsnpx skills add VoDaiLocz/kilo-kit-mcp --skill code-agent-patternsgit clone --depth 1 https://github.com/VoDaiLocz/kilo-kit-mcpWrote 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.
[](https://agentmods.dev/skills/vodailocz/kilo-kit-mcp/code-agent-patterns)<a href="https://agentmods.dev/skills/vodailocz/kilo-kit-mcp/code-agent-patterns"><img src="https://agentmods.dev/badge/skills/vodailocz/kilo-kit-mcp/code-agent-patterns.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00045 | $0.00814 |
| Opus 5 | $0.00023 | $0.00407 |
| Sonnet 5 | $0.00009 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
code-agent-patterns 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonomous Code Agent Patterns
Overview
The code-agent-patterns skill provides a standardized architectural framework for building, maintaining, and scaling autonomous Software Engineering (SWE) agents. It focuses on reliability, precision, and contextual awareness, drawing heavily from industry benchmarks like SWE-Bench and modern LLM-driven development tools.
When To Use
- Implementing autonomous code editing agents.
- Designing specialized agents for bug localization or patch generation.
- Orchestrating multi-agent systems for code review or testing.
- Building tools that need to interface with existing large codebases.
Core Patterns
1. Minimal Context Assembly
Avoid dumping the entire repository into the LLM context. Instead:
- Use dependency graph analysis to identify "impact zones."
- Implement "Breadth-First Context Discovery" (start with high-level symbols, drill down only when necessary).
- Support dynamic file inclusion based on the specific task (e.g., test files, related interfaces).
2. Symbol-Level Repository Indexing
Build a robust index that enables the agent to navigate the codebase as a human developer would:
- Symbol Maps: Index classes, functions, and interfaces along with their file locations.
- Call Graphs: Track function calls and dependencies to understand side effects.
- AST Analysis: Utilize Abstract Syntax Tree (AST) parsing to ensure structural awareness during code modifications.
3. Unified Diff & Search-Replace Patching
To minimize hallucination and merge conflicts:
- Prefer "Search-Replace" blocks over entire file rewrites.
- Validate that the "Search" block matches exact file content before applying the "Replace" content.
- Use unified diffs as a secondary representation for human review.
TDD Fix Loop Workflow
Agents must follow a strict "Red-Green-Refactor" loop for any bug fix:
- Reproduce: Write a test case that captures the reported bug (assert failure).
- Localize: Identify the source using logs, stack traces, or symbol-level search.
- Patch: Apply minimal code changes to satisfy the failing test.
- Verify: Run the test suite.
- Rollback: If tests fail after patching, discard changes and restart the process.
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.
- 4d ago First seen · 67 lines · 45 tokens per session scan A 6e4e0db9b744
code-agent-patterns is a skill published in the GitHub repository VoDaiLocz/kilo-kit-mcp (27 stars, last pushed yesterday), licensed Apache-2.0. It adds 45 tokens to every session and 814 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 2026-08-30.
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