Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/matteotitta/genesys-skillsnpx agentmods add skills/matteotitta/genesys-skills/gbp-suiteWrote 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/gbp-suite)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/gbp-suite"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/gbp-suite/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/gbp-suite"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/gbp-suite.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 | $0.00120 | $0.06377 |
| Opus 5.5 | $0.00048 | $0.02551 |
| Sonnet 5.5 | $0.00024 | $0.01275 |
| Haiku 4.5 | $0.00012 | $0.00638 |
Grade A, and why
gbp-review-strategy 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 — 693 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research source (Exa)
Default: Exa, per .claude/rules/exa-protocol.md (auto-loaded for research, audit, competitor, ICP, AEO, content sourcing, sales prospecting work).
Primary Exa tools for this skill: web_search_exa.
Use case: competitor review pattern research.
Tool surface during the migration window:
- New plugin (preferred):
mcp__plugin_exa_exa__web_search_exa(afterclaude plugin i exa@claude-plugins-official). - Legacy MCP (still mounted):
mcp__exa__web_search_exa. - Both backends route to the same Exa API — they don't double-bill.
Citation: every Exa-derived claim uses [VERIFIED: exa_search, {url}, accessed {YYYY-MM-DD}] per .claude/rules/ontology.md.
Quality gate (research outputs): ≥3 sources per major claim, ≥50% [VERIFIED] confidence, date filter for any "recent / latest" claim, no fallback to WebSearch without flagging the data gap.
Worked examples + tool catalog: .claude/skills/meta-skills/exa/.
GBP review strategy
Analyzes competitor review velocity, keyword mentions in reviews, neighborhood mentions, and recurring complaints. Then generates review response templates (5-star, 4-star, 3-star, 1-2 star) with 3 variations each that naturally incorporate service + location keywords. Covers article prompts #3 (competitor review teardown) and #4 (review response strategy) from the local SEO playbook.
Doctrine inherited (Step 7 — 0626 rollout, locked 2026-06-04)
Output complies with:
output-tenets.md,output-simplicity.md- Step 6 calibration: see [[feedback_execution_doctrine_refinements_step6]]
Refinements applied to this skill:
| Code | Refinement | How it lands in gbp-suite |
|---|---|---|
| R1 | Source placement | Review response templates → end-customer-facing (posted publicly on GBP). No source tags. |
| R2 | Single-doc-with-toggles | Multi-template pack ships as one doc with toggle per star tier. |
| R3 | Product-update tone | Responses frame as "we appreciate / we hear / we ship X" — operator-direct, never "we are thrilled." |
| R6 | CTA hierarchy | Response close → product-action (visit again, contact us) per customer-facing service business. |
| R7 | FAQ titles + no sources block | Competitor-review teardown article uses FAQ title pattern ("What review patterns work for [vertical]?"). |
| R8 | Entity-name headings | Section headings repeat business name where applicable. |
| R9 | Action-oriented section names | Response template names verb-led. |
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 · 693 lines · 120 tokens per session scan A e5611d60c6e1
gbp-review-strategy is a skill published in the GitHub repository matteotitta/genesys-skills (46 stars, last pushed 13d ago), licensed MIT. It adds 120 tokens to every session and 6,377 once invoked, about $0.0005 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 2026-09-03.
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