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 KCNyu/clawock --skill openclawgit clone --depth 1 https://github.com/KCNyu/clawockWrote 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/kcnyu/clawock/openclaw)<a href="https://agentmods.dev/skills/kcnyu/clawock/openclaw"><img src="https://agentmods.dev/badge/skills/kcnyu/clawock/openclaw/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/kcnyu/clawock/openclaw"><img src="https://agentmods.dev/badge/skills/kcnyu/clawock/openclaw.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Data Exfiltration · line 96 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
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 | $0.00036 | $0.01351 |
| Opus 5.5 | $0.00014 | $0.00540 |
| Sonnet 5.5 | $0.00007 | $0.00270 |
| Haiku 4.5 | $0.00004 | $0.00135 |
Grade A, and why
investment-decision 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
clawock investment-decision
You are the model side of a clawock decision run. Your runtime (OpenClaw) owns conversation, memory and tools; clawock owns the decision contract. Your entire job is one file in, one file out.
When to run
A run prepare has written a request file (the request_file path it
printed, e.g. .clawock/work/<run_id>/request.json). Open it first; it tells
you. On a fresh machine the workspace must be created once first:
clawock init book --workflow investment-decision (see ../../README.md
— "From zero").
task— the decision contract (evidence, opposing case, bounded action, reconciled amounts)context.documents— the certified context, with per-file sha256 fingerprintsworkflow.parameters— gates likemin_supporting_evidence,min_opposing_evidence,max_confidence_without_primary_source
What to produce
Write decision.json at the workspace root — artifact paths are resolved
against the workspace root, not the request directory. The schema is the
package's investment-decision workflow; when in doubt, keep the fields
minimal and explicit:
{
"schema_version": 1,
"workflow": {"id": "investment-decision", "version": "1.1.0"},
"decision_id": "example-2026-08-08",
"as_of": "2026-08-08T08:00:00+00:00",
"subject": {"ticker": "EXAMPLE", "market": "US", "currency": "USD"},
"evidence": [
{"id": "filing-growth", "stance": "supporting",
"summary": "The latest filed revenue figure grew year over year.",
"source": "issuer filing", "source_class": "primary",
"observed_at": "2026-08-08T07:30:00+00:00"},
{"id": "valuation-risk", "stance": "opposing",
"summary": "The current market multiple is above its stated range.",
"source": "market data snapshot", "source_class": "market",
"observed_at": "2026-08-08T07:45:00+00:00"}
],
"debate": {
"bull_case": {"summary": "Filed growth supports continued monitoring.",
"evidence_ids": ["filing-growth"]},
"bear_case": {"summary": "Valuation leaves insufficient margin of safety.",
"evidence_ids": ["valuation-risk"]}
},
"thesis": {
"statement": "Momentum is constructive, but price does not compensate for valuation risk.",
"confidence": 0.7,
"invalidation_conditions": ["Filed growth reverses"]
},
"decision": {
"action": "watch",
"rationale": "The opposing valuation evidence blocks an entry.",
"evidence_ids": ["filing-growth", "valuation-risk"],
"order": null
}
}
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 · 120 lines · 36 tokens per session scan A fdae32279755
investment-decision is a skill published in the GitHub repository KCNyu/clawock (21 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 1,351 once invoked, about $0.0001 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 2026-08-30.
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