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 soulcodex/agentic --skill project-mapgit clone --depth 1 https://github.com/soulcodex/agenticWrote 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/soulcodex/agentic/project-map)<a href="https://agentmods.dev/skills/soulcodex/agentic/project-map"><img src="https://agentmods.dev/badge/skills/soulcodex/agentic/project-map/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/soulcodex/agentic/project-map"><img src="https://agentmods.dev/badge/skills/soulcodex/agentic/project-map.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 | $0.00049 | $0.00898 |
| Opus 5.5 | $0.00020 | $0.00359 |
| Sonnet 5.5 | $0.00010 | $0.00180 |
| Haiku 4.5 | $0.00005 | $0.00090 |
Grade A, and why
project-map 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Map Skill
Generate .agentic/project-map.md to orient any agent to the codebase.
Step 0 — Check Existing Map
Check if .agentic/project-map.md already exists:
- If present: Ask the user if they want to refresh it or keep existing.
- Default: keep existing unless
--refreshflag is passed or user explicitly requests refresh.
- Default: keep existing unless
- If absent: Continue to Step 1.
Step 1 — Auto-discover Codebase Structure
Detect the language and architecture by inspecting the filesystem:
-
Detect language(s) — inspect for manifest files:
go.mod→ Gopackage.json/tsconfig.json→ TypeScript/JavaScriptpyproject.toml→ Pythoncomposer.json→ PHP
-
Detect architecture markers — inspect directory names:
- Hexagonal:
domain/,application/,infrastructure/,ports/ - CQRS:
command/,query/ - DDD: aggregate roots, value objects, domain events
- Hexagonal:
-
Read build/test/lint commands — inspect:
Makefilejustfilepackage.json scriptsTaskfile.yml
-
Identify entry points — look for:
main.gocmd/src/index.tsapp/main.pyartisanbin/
-
For monorepos — detect tier structure from
.agentic/config.yamlif present.
Step 2 — Map the Layer Structure
-
Identify architectural layers:
- Domain: entities, value objects, domain events, repository interfaces
- Application: use cases, command/query handlers
- Infrastructure: repository implementations, HTTP clients, messaging adapters
- Ports/Adapters: HTTP controllers, CLI commands, message consumers
-
List key modules/packages (top 5-10) with one-line purpose each.
-
Note non-obvious conventions:
- Naming rules (e.g.,
*_test.gosuffix,service.gopatterns) - File organization (co-location rules, split by concern vs. feature)
- Error handling patterns
- Token/entity naming conventions
- Naming rules (e.g.,
Step 3 — Identify Complexity Hotspots
- Largest files by line count — use
wc -lor equivalent on key source 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.
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 · 107 lines · 49 tokens per session scan A 0748ce817c89
project-map is a skill published in the GitHub repository soulcodex/agentic (10 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 898 once invoked, about $0.0002 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
repo-onboarding
Systematically map an unfamiliar codebase before changing it — entry points, build/test loop, conventions, data flow. Use when starting work in a repo you haven't seen, or asked "how does this codebase work?".
context-builder
Gather comprehensive project context before starting implementation. Use at the beginning of complex tasks to understand codebase structure, dependencies, patterns, and conventions before writing code.
help
Use when asked what the capstone plugin can do - prints the usage block.
start
Use when the user says just "capstone" with nothing else, or asks to start or continue the capstone pipeline - runs the greenfield chain one stage at a time, detecting completed stages and resuming at the first incomplete one. A stage word as the argument (mockup, logic, uiux, architecture, standards, stack, build)…
feature
Use when the user wants one feature taken from idea to working code - "add a feature", "build X end to end", "take X from idea to shipped" - runs the feature chain groom → plan → implement consecutively, detecting the feature's stage and resuming at the first incomplete one. For the whole-product greenfield pipeline…
review
Use when asked for an opinionated review of the codebase - architecture/backend findings, UI findings against the project's own design docs, or both - severity-ranked with evidence, written to docs/capstone/review.md. Bare "review" does both sides; "review backend" or "review frontend" does one. "review retro…