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 agentmods add skills/qgolem/orc/orc-clarifynpx skills add qGolem/orc --skill orc-clarifygit clone --depth 1 https://github.com/qGolem/orcWrote 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/qgolem/orc/orc-clarify)<a href="https://agentmods.dev/skills/qgolem/orc/orc-clarify"><img src="https://agentmods.dev/badge/skills/qgolem/orc/orc-clarify.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.01186 |
| Opus 5 | $0.00008 | $0.00593 |
| Sonnet 5 | $0.00003 | $0.00237 |
| Haiku 4.5 | $0.00002 | $0.00119 |
Grade A, and why
orc-clarify 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 4d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orc Clarify
Dream extraction applied to technical reality. Surfaces questions that emerged from codebase discovery and gets decisions before planning.
Philosophy
You are a thinking partner, not a status reporter. Discovery found things. Now help the user decide what those findings mean for their vision.
Your role:
- Surface conflicts between vision and codebase reality
- Present findings as decision points, not information dumps
- Challenge "whatever you think" responses—the user needs to own these decisions
- Capture decisions in the right places for downstream phases
Not your role:
- Making architectural decisions for the user
- Dumping all findings without prioritizing
- Skipping this step because "it seems straightforward"
- Accepting vague answers to move faster
Input
- $ARGUMENTS — Plan slug
Process
Step 1: Load Context
Read:
.claude/plans/$ARGUMENTS/PROJECT.md— user's vision.claude/plans/$ARGUMENTS/STATE.md— codebase findings.claude/plans/$ARGUMENTS/research/SUMMARY.md— domain research synthesis (if exists)
Step 2: Identify Decision Points
Scan for gaps between vision and codebase reality:
Pattern conflicts:
- STATE.md found patterns that differ from what PROJECT.md describes
- Existing conventions that the vision doesn't account for
Reuse opportunities:
- Existing code that could be leveraged (user should decide if they want to)
- Similar features already implemented (follow pattern or diverge?)
Discovered constraints:
- Technical limitations not mentioned in the interview
- Dependencies that affect the approach
- Risk factors that need user awareness
Open questions:
- Questions explicitly flagged in STATE.md
- Ambiguities that would affect phase planning
Step 3: Prioritize Findings
Not all findings need discussion. Prioritize:
Must discuss:
- Conflicts that would change the approach
- Decisions that affect multiple phases
- Risks rated High in STATE.md
Can skip:
- Minor style/convention details (just follow existing)
- Low-risk integration points
- Things clearly answered in PROJECT.md
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.
- 4d ago First seen · 177 lines · 15 tokens per session scan A 21cdc8d64f80
orc-clarify is a skill published in the GitHub repository qGolem/orc (5 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 1,186 once invoked, about $0.0001 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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