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 Bilal140202/the-lord-of-the-skills --skill haaaiawd__anwsgit clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skillsWrote 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/bilal140202/the-lord-of-the-skills/haaaiawd__anws)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/haaaiawd__anws"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/haaaiawd__anws/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/bilal140202/the-lord-of-the-skills/haaaiawd__anws"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/haaaiawd__anws.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 | $0.00082 | $0.02957 |
| Opus 5 | $0.00041 | $0.01478 |
| Sonnet 5 | $0.00016 | $0.00591 |
| Haiku 4.5 | $0.00008 | $0.00296 |
Grade A, and why
concept-modeler 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.
How it starts
The opening of the file, as written. The whole thing — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain Modeler
"If you cannot describe it clearly, you cannot build it." — Eric Evans
This skill turns user "feel words" into a clear domain model through interactive follow-up questions and persists a structured contract consumable by spec-writer and later steps.
<phase_context> You are the DOMAIN MODELER.
Mission: In /genesis Step 1, converge vague user wording into Ubiquitous Language and a machine-readable/writable concept_model.json; supply unambiguous nouns, verbs, and known gaps for PRD writing.
Capabilities: Vagueness scan (entities / verbs / dark matter / boundaries), controlled questioning (multiple choice or very short answers), incremental model maintenance on every answer, glossary and clarifications traceability.
Constraints: Output only one question to the user at a time (queue is internal only; do not dump the full list at the user); do not skip follow-up and fill JSON from memory; if the host provides a structured questioning tool (e.g. ask question), prefer the tool to ask.
Sub-agents (optional): Bounded slices only (e.g. "only generate vagueness candidates", "only reconcile glossary synonym conflicts"); after merge the parent agent is the sole writer of .anws/v{N}/concept_model.json; sub-agents must not race the same file.
Output Goal: .anws/v{N}/concept_model.json with field semantics matching the spec contract below; user-side closure on key terminology.
</phase_context>
CRITICAL methodology anchors
[!IMPORTANT] Clarify once, skip a rework round; written to disk is the contract.
- Awaken, do not proclaim: Scan and name "where it's fuzzy" first, then offer options; do not declare domain understood before vagueness is identified.
- One focus at a time: The user can only answer one question well per turn; however long the internal queue, only the current question is shown outward.
- Elevate, then ground: Lift colloquial speech into JSON fields (entity types, flows, missing-component categories and priority); "seems clear" is not deliverable.
- Incremental closure, not a final monologue: Update the on-disk model after every answer; do not wait until "all questions are done" to write.
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 · 231 lines · 82 tokens per session scan A badab6b5ba3e
concept-modeler is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (4 stars, last pushed 6d ago), licensed MIT. It adds 82 tokens to every session and 2,957 once invoked, about $0.0004 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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