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 OneWave-AI/claude-skills --skill champion-identifiergit clone --depth 1 https://github.com/OneWave-AI/claude-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/onewave-ai/claude-skills/champion-identifier)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/champion-identifier"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/champion-identifier/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/onewave-ai/claude-skills/champion-identifier"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/champion-identifier.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 | $0.00048 | $0.00460 |
| Opus 5 | $0.00024 | $0.00230 |
| Sonnet 5 | $0.00010 | $0.00092 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
champion-identifier 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 — 31 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Champion Identifier
Find the internal champion most likely to advocate for the solution at a target account, using structured LinkedIn and account analysis.
Contents
- references/scoring-framework.md - champion profile, six scoring dimensions, total-score bands, warning signs
- references/output-template.md - the full Markdown report structure to produce
- references/outreach-templates.md - warm-intro, forwardable, direct, and opening-line messages
- references/meeting-prep.md - discovery and qualification questions, red flags
- references/multi-threading.md - sequence, coverage map, DMU table, org-chart format
- references/champion-development-plan.md - five-phase plan with success metrics
- references/playbook.md - tips, best practices, trigger phrases, worked example
Workflow
- Gather inputs: the company, the solution being sold, and any known contacts or mutual connections. Ask for whatever is missing.
- Research the company and the department the solution touches: stage, recent news, likely pain points, decision-making style, and hiring signals.
- Identify 5-10 candidate individuals on LinkedIn within the relevant department and leadership chain.
- Score each candidate across the six dimensions (0-10 each, 0-60 total) per references/scoring-framework.md, citing concrete evidence for every score.
- Rank candidates best to worst, and flag anyone who is a blocker or coach rather than a champion using the warning signs.
- For the top candidates, choose an outreach path (warm intro vs. direct) and draft the message from references/outreach-templates.md, plus personalization hooks and meeting prep from references/meeting-prep.md.
- Build the multi-threading plan and account map (DMU table, org chart) per references/multi-threading.md.
- Assemble the full report following references/output-template.md, filling every field with researched specifics and no placeholders.
- Recommend next steps using the phased plan in references/champion-development-plan.md.
What ships with it
7 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.
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 · 31 lines · 48 tokens per session scan A c34b1e58577a
champion-identifier is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 460 once invoked, about $0.0002 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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