Borrowing it
Nothing to install: this file belongs to doncheli/don-cheli-sdd. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/doncheli/don-cheli-sdd/main/.agent/skills/doncheli-distill/SKILL.mdgit clone --depth 1 https://github.com/doncheli/don-cheli-sddWrote 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/doncheli/don-cheli-sdd/doncheli-distill)<a href="https://agentmods.dev/skills/doncheli/don-cheli-sdd/doncheli-distill"><img src="https://agentmods.dev/badge/skills/doncheli/don-cheli-sdd/doncheli-distill/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/doncheli/don-cheli-sdd/doncheli-distill"><img src="https://agentmods.dev/badge/skills/doncheli/don-cheli-sdd/doncheli-distill.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 | $0.00056 | $0.00416 |
| Opus 5 | $0.00028 | $0.00208 |
| Sonnet 5 | $0.00011 | $0.00083 |
| Haiku 4.5 | $0.00006 | $0.00042 |
Grade A, and why
doncheli-distill 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 12d 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.
What it actually says
Don Cheli: Blueprint Distillation
Instructions
- Identify the target module, service or codebase to distill
- Scan entry points (routes, controllers, event handlers, CLI commands)
- Trace data flows: inputs → transformations → outputs → side effects
- Identify implicit business rules embedded in conditionals, validations, error handling
- Map entity relationships from data models and DB schemas
- Generate Gherkin scenarios that describe the observed behavior (not the code)
- Produce a C4-style architecture diagram in text (Mermaid or ASCII)
- Flag ambiguities, dead code, and undocumented assumptions with
[NEEDS CLARIFICATION]
Output Format
## Blueprint: <module/service name>
### Architecture Diagram
```mermaid
…
Distilled Spec (Gherkin)
Feature: <name>
Background: …
Scenario: <happy path>
Given …
When …
Then …
Scenario: <edge case / sad path>
…
Implicit Business Rules
- — found in: file:line …
Ambiguities & Dead Code
- [NEEDS CLARIFICATION] — file:line …
## Quality Gate
- Every entry point must map to at least one Gherkin scenario
- Architecture diagram must show at least: external inputs, internal modules, data stores, external services
- Business rules must cite their source location
## Do not use this skill when
- The user wants to write new specs for a new feature (use doncheli-spec instead)
- The codebase has no existing logic to analyze
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.
- 12d ago First seen · 62 lines · 56 tokens per session scan A 06c736cc6285
doncheli-distill is a skill published in the GitHub repository doncheli/don-cheli-sdd (57 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 416 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 2026-08-30.
Other skills, from other repositories
autonomous
Run multiple phases hands-free. Chains discuss, plan, build, and verify automatically.
quick
Execute an ad-hoc task with atomic commits. Skips full plan/review.
debug
Systematic debugging with hypothesis testing. Persistent across sessions.
explore
Explore ideas, think through approaches, and route insights to the right artifacts.
resume
Pick up where you left off. Restores context and suggests next action.
audit
Review past Claude Code sessions for PBR workflow compliance and UX quality.