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 matteotitta/genesys-skills --skill competitor-researchgit clone --depth 1 https://github.com/matteotitta/genesys-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/matteotitta/genesys-skills/competitor-research)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/competitor-research"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/competitor-research/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/matteotitta/genesys-skills/competitor-research"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/competitor-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Agent Snooping · line 165 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00024 | $0.02969 |
| Opus 5 | $0.00012 | $0.01484 |
| Sonnet 5 | $0.00005 | $0.00594 |
| Haiku 4.5 | $0.00002 | $0.00297 |
Grade A, and why
competitor-research 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 9d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor research
Run a 13-dimension dossier on a B2B SaaS competitor. Output ships with explicit confidence levels, inline source citations, a consolidated Sources & data quality table, and a data-gaps section with follow-up actions. Knowledge type: competitor-intel (per .claude/rules/ontology.md); maturity: emergent → validated after client review.
Research substrate
Default substrate: Exa (per .claude/rules/exa-protocol.md, auto-loaded). Primary tools: find_similar_links_exa (structural competitor discovery from a client URL), web_search_exa (news, voice, gap discovery), web_fetch_exa (clean comparison-page extraction). Crawl-cost discipline (.claude/rules/crawl-cost-discipline.md): when a dimension needs a competitor's page inventory (Content, SEO/AEO), enumerate pages first with free mcp__spider__spider_links (local, no credits), triage to product / pricing / positioning / customer pages, then spend web_fetch_exa / Firecrawl only on kept pages — this kills the "fallback to Apify if credits exhausted" failure on large sites. Migration window: prefer the plugin namespace mcp__plugin_exa_exa__* once installed; legacy mcp__exa__* still mounted as fallback. Worked examples + tool catalog: .claude/skills/meta-skills/exa/.
When to run
Invoke when the user asks for: competitor analysis for X, battlecard research for X, competitive landscape for [market], compare X vs Y, what's [competitor] doing?. Do NOT invoke for: company qualification (use /company-context), product messaging only (use /product-messaging), researching the user's own company (use /company-context), or single-feature questions (answer directly).
Three run modes — pick by cadence and depth needed:
- First run (~90 min) —
/competitor-research [competitor]. New competitor, no existing dossier. Phases 1–3 (or 1–4 for aggregate). - Quick scan (~30 min, weekly) —
/competitor-research --quick [competitor]or/loop 1w. Refreshes fast-moving data only (news, Clay, G2, internal sources). Updates "Recent changes" header — sections without changes stay untouched. - Deep refresh (~90 min, monthly) —
/competitor-research --refresh [competitor]or/loop 1M. Full 13-dimension cycle with TrustPilot monitor and Phase 4 aggregate (if 2+ competitors refreshed this cycle).
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.
- 9d ago First seen · 175 lines · 136 tokens per session scan A c921d85ca38a
competitor-research is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 2,969 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 2026-09-03.
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