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 skills add varunk130/ai-workflow-playbooks --skill codebase-navigationgit clone --depth 1 https://github.com/varunk130/ai-workflow-playbooksWrote 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/varunk130/ai-workflow-playbooks/codebase-navigation)<a href="https://agentmods.dev/skills/varunk130/ai-workflow-playbooks/codebase-navigation"><img src="https://agentmods.dev/badge/skills/varunk130/ai-workflow-playbooks/codebase-navigation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/varunk130/ai-workflow-playbooks/codebase-navigation"><img src="https://agentmods.dev/badge/skills/varunk130/ai-workflow-playbooks/codebase-navigation.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00020 | $0.00837 |
| Opus 5.5 | $0.00008 | $0.00335 |
| Sonnet 5.5 | $0.00004 | $0.00167 |
| Haiku 4.5 | $0.00002 | $0.00084 |
Grade A, and why
codebase-navigation 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 1mo 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Navigation
What This Skill Enables
An agent that can quickly orient itself in any codebase - finding the right files, understanding the architecture, and identifying conventions - before writing a single line of code. Agents without this skill guess at file locations, miss existing utilities, and create duplicates.
Core Competencies
1. Project Reconnaissance
Before touching code, build a mental map:
- Read
README.md,CONTRIBUTING.md, and any project-level config files - Identify the package manager and build system (
package.json,pyproject.toml,Cargo.toml,go.mod) - Map the directory structure - where does source live? Tests? Config? Docs?
- Identify the entry point(s) of the application
2. Convention Detection
Infer the project's conventions from existing code:
- Naming: camelCase vs snake_case vs kebab-case - match what exists
- File organization: feature-based vs layer-based vs hybrid
- Import style: relative vs absolute, barrel files, path aliases
- Testing conventions: co-located tests vs separate
__tests__directory, naming patterns - Error handling: custom error classes, result types, try/catch patterns
3. Dependency Mapping
Trace how components connect:
- Follow imports from the entry point to understand the call graph
- Identify shared utilities and where they live
- Locate configuration and environment variable usage
- Map database models/schemas to their consumers
- Identify external API integrations and their client modules
4. Search Strategies
Use the right tool for each search type:
| Goal | Strategy |
|---|---|
| Find a file by name | Glob patterns: **/UserService.*, **/*.config.* |
| Find where a function is defined | Grep for function name( or def name or class Name |
| Find where a function is called | Grep for the function name, exclude the definition file |
| Understand data flow | Start at the API endpoint, follow the handler chain inward |
| Find related tests | Look for files matching *.test.*, *.spec.*, or test_* near the source |
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.
- 1mo ago First seen · 71 lines · 20 tokens per session scan A 8b586f527420
codebase-navigation is a skill published in the GitHub repository varunk130/ai-workflow-playbooks (2 stars, last pushed 24d ago), licensed MIT. It adds 20 tokens to every session and 837 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
customer-journey-map
Construye un mapa de recorrido del cliente para un producto, servicio o experiencia. Úsalo cuando se te pida mapear un recorrido del cliente, crear un viaje del usuario, documentar puntos de contacto y puntos de fricción, o diseñar un mapa de experiencia. Produce un mapa de recorrido completo con etapas, puntos de…
user-story-writer
Escribir historias de usuario bien estructuradas con criterios de aceptación y casos extremos. Úsalo cuando te pidan escribir historias de usuario, crear tickets a partir de un resumen de características, convertir un PRD en historias o redactar criterios de aceptación. Produce historias listas para estimar en formato…
feature-prioritisation
Aplica marcos de priorización (RICE, MoSCoW, Kano, ICE, Opportunity Scoring) para clasificar características e items del backlog. Úsalo cuando se te pida priorizar características, clasificar un backlog, decidir qué construir a continuación, o evaluar compensaciones entre ideas competidoras. Produce una lista de…
morning-intelligence
Interviews you across 15 questions to capture your role, topics, sources, exclusions, and format preferences, then writes a master prompt you can paste into a scheduled task or Claude Code Routine. Use when you want to set up a personalised daily news brief, build a reusable morning news prompt, or create an automated…
data-analysis-standard
Estructura un análisis de datos de producto, análisis profundo de métricas, análisis de embudo o estudio de cohortes. Úsalo cuando te pidan analizar métricas de producto, investigar una caída en conversión, explicar un cambio de datos a stakeholders o encontrar la causa raíz de un movimiento de métrica. Produce un…
technical-spec-template
Crea documentos de especificación técnica estructurados que conectan requisitos de producto con implementación de ingeniería. Úsalo cuando escribas una especificación técnica, especificación de ingeniería, documento de diseño de sistema o especificación de API. Produce una especificación completa con declaración del…