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/vincentkoc/dotskills/openclaw-github-dedupenpx skills add vincentkoc/dotskills --skill openclaw-github-dedupegit clone --depth 1 https://github.com/vincentkoc/dotskillsWrote 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/vincentkoc/dotskills/openclaw-github-dedupe)<a href="https://agentmods.dev/skills/vincentkoc/dotskills/openclaw-github-dedupe"><img src="https://agentmods.dev/badge/skills/vincentkoc/dotskills/openclaw-github-dedupe.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 | $0.00068 | $0.05711 |
| Opus 5 | $0.00034 | $0.02856 |
| Sonnet 5 | $0.00014 | $0.01142 |
| Haiku 4.5 | $0.00007 | $0.00571 |
Grade A, and why
openclaw-github-dedupe 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 — 501 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Issue/PR Cluster Deduper
Use this skill when a cluster of GitHub issues and pull requests has been reported for a common failure mode (Slack, iMessage, support threads, or manual list), and you need an evidence-based dedupe recommendation, execution pass, or autonomous closeout run.
Purpose
Provide a consistent, evidence-driven triage pass for issue and PR clusters so duplicate work is folded, contributor credit is preserved, and cleanup actions stay auditable.
Execution is command-led and conservative: drive decisions from gh readbacks plus deterministic file/metadata checks only, and avoid speculative local analysis beyond triage logic.
Autonomous mode is different from broad dedupe: it starts from user-provided links/refs, follows only links found inside those refs, first decides whether the cluster is still viable and needed against current main, then drives the selected fix/merge/closure path to completion when repo policy allows.
Primary goal: make every run action-ready with explicit per-item actions, links, and command outcomes.
Vision
Treat each cluster as a triage system, not a documentation exercise. The expected behavior is deterministic classification, auditable comment text, safe mutation flow, and fast operator comprehension.
Principles (read before execution)
These are defined in principles.md:
- Evidence over narrative
- Root-cause alignment over title similarity
- Credit-preserving attribution
- Safe defaults (
dry-runand blockers) - Complete audit trail in comments and labels
- Humans first: communicate like a senior developer advocate, not a script.
Read constitution.md for governance requirements and decision quality rules before choosing final outcomes.
Operator experience and communication defaults
This workflow is designed for high-velocity maintainers and external contributors:
- Keep every reply short, clear, and respectful.
- Lead with what happened, then why.
- Include a plain-English next step and reopen path.
- Avoid abrupt or accusatory language, especially on duplicates.
- Never hide uncertainty; if blocked, say what is missing and what you need next.
- Treat the assistant as a Developer Experience lead: helpful, practical, and direct without sounding mechanical.
- Use examples as style guidance, not templates to paste verbatim.
- Vary sentence ordering and opener lines per message so repeated runs do not sound identical.
- Do not repeat the exact same message body twice in one cluster run unless no safe variation is possible.
- Use short, conversational paragraphs (2-4 paragraphs), and avoid one-liner robotic templates.
- If intent is clear, keep tone warm and explanatory even when issuing a close.
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/cluster-decision-agent.md 742 B
- agents/cluster-evidence-agent.md 639 B
- agents/cluster-intake-agent.md 708 B
- agents/cluster-similarity-agent.md 2.1 KB
- agents/cluster-synthesis-agent.md 728 B
- agents/openai.yaml 472 B
- assets/icon.jpg 37 KB
- constitution.md 2.0 KB
- principles.md 1.6 KB
- scripts/alias.sh 7.6 KB runs code
- scripts/cluster-example.txt 446 B
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 · 501 lines · 68 tokens per session scan A a2dc805890a1
openclaw-github-dedupe is a skill published in the GitHub repository vincentkoc/dotskills (102 stars, last pushed 13d ago), licensed MIT. It adds 68 tokens to every session and 5,711 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.
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