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 thinkgit 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/think)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/think"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/think/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/think"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/think.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 | $0.00190 | $0.02976 |
| Opus 5 | $0.00095 | $0.01488 |
| Sonnet 5 | $0.00038 | $0.00595 |
| Haiku 4.5 | $0.00019 | $0.00298 |
Grade A, and why
think 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 10d 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/think — Temporal-trajectory queries against the brain
Answer "when did X last Y" / "what changed since Z" / "what's the latest on W" by splicing dated entries from client history.md, sprint goals/MMYY-NN-cycle.md, memory pages, and session decisions into a chronological timeline. Zero LLM cost on intent classification — regex routes the query, the splice does the work.
Stolen from garrytan/gbrain (v0.40.2.0) via /steal Phase 5–6 (2026-05-23). See .claude/discovery/0526-gbrain-steal-analysis.md item G19.
Triggers
Invoke this skill when the user says:
/think [question]- "When did Alan last push back on positioning?"
- "When was the last time we shipped a Pulse?"
- "What changed in ClientCo's pricing since the March doc?"
- "What's the latest on ClientCo's GTM stack build?"
- "Any new on ClientCo?"
- "What happened with the Notion shadow-pull thing?"
Do NOT invoke when:
- The question is rule-shaped or convention-shaped ("do we have a rule about X?") — use
/recall --memory - The question is decision-extraction shaped ("what did we decide about X?") — use
/recall --decisions - The question is research-shaped or external ("what's Salesloft launching this week?") — follow
.claude/rules/brain-first-lookup.mdthen Exa perexa-protocol.md - The question is in-session reasoning ("what should we do next?") — just answer
If unsure between /think and /recall: /think is for when-shaped and what-changed-shaped questions; /recall is for what-was-decided and what-was-discussed questions.
Process
Step 1 — Classify intent (regex, zero-LLM)
Apply the classifier to the input question. Three intents:
| Intent | Regex pattern (case-insensitive) | Routing |
|---|---|---|
| temporal | `\b(when | last time |
| knowledge_update | `\b(latest | recent |
| other | (no match) | Fast-path: short-circuit to /recall <topic> |
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.
- 10d ago First seen · 227 lines · 190 tokens per session scan A d8c1e8ab6acc
think is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 190 tokens to every session and 2,976 once invoked, about $0.0010 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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