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 kucherenko/gangsta --skill reconnaissancegit clone --depth 1 https://github.com/kucherenko/gangstaWrote 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/kucherenko/gangsta/reconnaissance)<a href="https://agentmods.dev/skills/kucherenko/gangsta/reconnaissance"><img src="https://agentmods.dev/badge/skills/kucherenko/gangsta/reconnaissance/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/kucherenko/gangsta/reconnaissance"><img src="https://agentmods.dev/badge/skills/kucherenko/gangsta/reconnaissance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00043 | $0.02256 |
| Opus 5 | $0.00022 | $0.01128 |
| Sonnet 5 | $0.00009 | $0.00451 |
| Haiku 4.5 | $0.00004 | $0.00226 |
Grade A, and why
reconnaissance 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 10d 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reconnaissance: Intel and Environment Mapping
Overview
Every Heist begins with gathering intel. The Underboss deploys Associates to perform a detailed survey of the target codebase and infrastructure. The output is a Reconnaissance Dossier that informs all subsequent phases.
Trigger
Invoked when the Don expresses building or creative intent.
Process
Step 1: Analyze Intent
The Underboss parses the Don's request to identify:
- Objective: What is being built or changed?
- Scope: Which parts of the system are affected?
- Constraints: Any explicit requirements or limitations?
Step 2: Deploy Associates
Dispatch Associate subagents in parallel to gather intel.
Subagent type: Use subagent_type: "associate" for all Associate dispatches. Do NOT use "general" or "general-purpose" — these are not valid in a Gangsta installation.
Greenfield Mode (empty or near-empty workspace)
Before dispatching the standard survey, count the files in the working directory (excluding .git, docs/gangsta/, and other meta directories).
Trigger: the workspace contains fewer than 5 source files OR no recognizable project manifest (package.json, requirements.txt, go.mod, Cargo.toml, pyproject.toml, etc.).
When the trigger fires, the reconnaissance objective shifts from "survey the existing code" to "sharpen the IDEA". The standard codebase survey is still run (to capture what little exists), but it is no longer the center. Instead, deploy these associates in parallel:
| Associate Task | What to Investigate |
|---|---|
| Idea Framing | Restate the Don's objective in the Don's own words. Identify the problem being solved, who has it, and what evidence (if any) the Don offered. Surface hidden assumptions. |
| Analogues | Search the internet for existing tools, libraries, products, or papers that solve the same or adjacent problems. For each analogue: name, what it does, what it gets right, what it gets wrong, license/hosting model. Use the webfetch tool. Produce at least 3 analogues; if fewer than 3 exist, say so and explain why the space is sparse. |
| Prior Art & Patterns | Search the internet for relevant prior art: protocols, data formats, algorithms, design patterns, prior attempts, postmortems. Cite sources (URLs). |
| Constraint & Risk Survey | Enumerate known constraints for the domain: performance ceilings, security concerns, regulatory, accessibility, platform limits. Cite sources. |
| Codebase Structure | (Standard survey — what little exists in the workspace.) |
| Ledger Search | (Standard survey.) |
| Constitution | (Standard survey.) |
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.
- 10d ago First seen · 227 lines · 43 tokens per session scan A 55aead2d0434
reconnaissance is a skill published in the GitHub repository kucherenko/gangsta (81 stars, last pushed 27d ago), licensed MIT. It adds 43 tokens to every session and 2,256 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.
Other skills, from other repositories
cocotrace
Build and query the SHA-256 requirements-to-implementation traceability graph across lifecycle artifacts.
context-add
Guided wizard to capture or update organizational Snowflake/Cortex standards into .cocoplus/context/ .md. Presents a menu of 6 standard types, collects answers via multi-turn dialogue, and commits the file.
lean-review
CocoLean diff-scoped over-engineering audit — scans uncommitted git diff and applies five classification tags (delete/stdlib/native/yagni/shrink) to identify unnecessary surface area before commit.
cocoplus-config
CocoPlus configuration SSOT — $cocoplus sync propagates cocoplus.toml into downstream artifacts; $cocoplus migrate-config converts legacy safety-config.json. Invoked via $cocoplus sync and $cocoplus migrate-config.
bloom-crystallize
CocoBloom crystallization — converts a successful ship execution trace into a reusable skill file. Requires recent successful $ship. Invoked via $bloom crystallize.
discuss-red-team
CocoDiscuss Red-Team Mode — adversarial devil's advocate session that challenges spec assumptions before $plan. Invoked via $discuss --red-team.