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 AnthonyAlcaraz/agentic-graph-rag-skills --skill tool-primitive-selectorgit clone --depth 1 https://github.com/AnthonyAlcaraz/agentic-graph-rag-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/anthonyalcaraz/agentic-graph-rag-skills/tool-primitive-selector)<a href="https://agentmods.dev/skills/anthonyalcaraz/agentic-graph-rag-skills/tool-primitive-selector"><img src="https://agentmods.dev/badge/skills/anthonyalcaraz/agentic-graph-rag-skills/tool-primitive-selector/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/anthonyalcaraz/agentic-graph-rag-skills/tool-primitive-selector"><img src="https://agentmods.dev/badge/skills/anthonyalcaraz/agentic-graph-rag-skills/tool-primitive-selector.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00205 | $0.02675 |
| Opus 5 | $0.00102 | $0.01337 |
| Sonnet 5 | $0.00041 | $0.00535 |
| Haiku 4.5 | $0.00020 | $0.00267 |
Grade A, and why
tool-primitive-selector scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
command surface, Unix-pipe composable (`curl|jq|grep` beats four MCP calls), How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tool Primitive Selector
Overview
You have three distinct ways to give an agent a capability, and Ch6 is explicit that they are converging, not competing. The Google Workspace CLI is one tool with three interfaces: a CLI surface, a built-in MCP server mode, and 100+ prebuilt skills. So the question is rarely "which one?" but "which PRIMARY primitive, and what else should this ALSO be exposed as?"
Each primitive answers a different question for a different audience:
- CLI answers "how does the agent PERFORM this operation?" Deterministic
command surface, Unix-pipe composable (
curl|jq|grepbeats four MCP calls), self-describing via--help, invokable with no model in the loop. Models have internalized CLI grammar from millions of Stack Overflow answers and man pages. Costs ~400 tokens after dynamic discovery. Audience: the individual developer in build mode / CI, on a machine they trust. - MCP answers "how does the agent CONNECT to this service securely?" Model-callable server with schemas, runtime-discoverable, OAuth + scoped per-agent access control through gateways. Static schemas cost 23K-50K tokens before any reasoning, which is why runtime retrieval is mandatory at scale. Audience: enterprise teams, non-developer users, and unsupervised background agents that cannot be granted broad access.
- SKILL answers "WHAT should the agent do, and in what order?" Encoded judgment / procedure the model reads. Natural language, no install, ~100 tokens, works for everyone. It is the meta-layer that makes the other two effective. Author it first regardless.
The selector profiles a capability along the chapter's four dimensions — who
runs it, when, where, what access — plus a composability need, then scores the
three primitives across six feature axes (deterministic surface,
runtime-discoverable, access control, encodes judgment, personal fit, enterprise
fit). It returns a primary recommendation AND an also_expose_as list, and
places the audience on the personal-to-enterprise gradient with its governance
implication.
What ships with it
2 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.
- 11d ago First seen · 172 lines · 205 tokens per session scan A 2e3be606fd01
tool-primitive-selector is a skill published in the GitHub repository AnthonyAlcaraz/agentic-graph-rag-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 205 tokens to every session and 2,675 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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