code-intelligence

code-intelligence is a skill for Codex from TIKAZI/TIKAZ-AI-Skills. It costs 54 tokens per session (460 once invoked), scanned A, original, MIT.

A repository-analysis guide that maps how a codebase is organized and how its parts depend on one another.

In plain words
What is it for?
Use it to trace dependencies, review pull requests, plan refactors, and check changes with the project's tests, type checks, linting, and build commands.
Why use it?
It helps developers understand unfamiliar code and see which files may be affected before making changes.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to trace dependencies, review pull requests, plan refactors, and check changes with the project's tests, type checks, linting, and build commands.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tikazi/tikaz-ai-skills/code-intelligence
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.

Any agent
npx skills add TIKAZI/TIKAZ-AI-Skills --skill code-intelligence
Clone the repo
git clone --depth 1 https://github.com/TIKAZI/TIKAZ-AI-Skills

Made for: Codex.

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 code-intelligence

README.md
[![agentmods](https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/code-intelligence.svg)](https://agentmods.dev/skills/tikazi/tikaz-ai-skills/code-intelligence)
Your own site
<a href="https://agentmods.dev/skills/tikazi/tikaz-ai-skills/code-intelligence"><img src="https://agentmods.dev/badge/skills/tikazi/tikaz-ai-skills/code-intelligence.svg" alt="Measured on agentmods" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 460 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00054 $0.00460
Opus 5 $0.00027 $0.00230
Sonnet 5 $0.00011 $0.00092
Haiku 4.5 $0.00005 $0.00046

Measured 8d ago against content hash 9a548078b3d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

code-intelligence 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 8d 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.

suites/engineering/code-intelligence/SKILL.md · 40 lines

What it actually says

Code Intelligence

This public entry combines the local 代码-CodeGraph and 代码-GitNexus roles into one non-competing, clean-room workflow. This TIKAZ Edition is designed, integrated, refactored, and continuously maintained by TIKAZ.

Workflow

  1. Identify the repository, framework, entry points, tests, build commands, and local instructions.
  2. Build a compact map of modules, symbols, imports, data flow, and public boundaries.
  3. For a change, trace direct and indirect consumers before proposing edits.
  4. For a PR, review correctness, regressions, security, tests, and maintainability; cite files and lines.
  5. For a refactor, define invariants, migration steps, compatibility risks, and a rollback path.
  6. Validate with repository-native tests, type checks, lint, build, and focused impact checks.

Inputs and output contract

Accept a repository path or PR, the question or proposed change, and any known constraints. Return an evidence-backed architecture map, direct and indirect consumers, prioritized findings, an implementation or refactor plan, and verification results. Cite files and lines where possible; separate observed facts, inferences, and recommendations.

Validation and fallback

Cross-check the map against repository search, build metadata, tests, and call sites. If graph tooling is unavailable, fall back to repository-native search and explicit uncertainty rather than inventing relationships. Do not edit code unless the user also requests implementation.

Example

Use code-intelligence to map the authentication flow, find consumers of this API, and identify refactor risks before any edits.

Limits

Static analysis can miss runtime reflection, generated code, environment-specific wiring, and external consumers. Mark these gaps.

Source note

This role was written independently after studying the problem space. CodeGraph and GitNexus are research references only; no GitNexus code or documentation is distributed here.

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 40 lines · 54 tokens per session scan A 9a548078b3d8

Subscribe to this mod's changes

code-intelligence is a skill published in the GitHub repository TIKAZI/TIKAZ-AI-Skills (6 stars, last pushed 5d ago), licensed MIT. It adds 54 tokens to every session and 460 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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