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 slhaf/AgenticGPT --skill skill-installergit clone --depth 1 https://github.com/slhaf/AgenticGPTWrote 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/slhaf/agenticgpt/skill-installer)<a href="https://agentmods.dev/skills/slhaf/agenticgpt/skill-installer"><img src="https://agentmods.dev/badge/skills/slhaf/agenticgpt/skill-installer/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/slhaf/agenticgpt/skill-installer"><img src="https://agentmods.dev/badge/skills/slhaf/agenticgpt/skill-installer.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 | $0.00017 | $0.00537 |
| Opus 5.5 | $0.00007 | $0.00215 |
| Sonnet 5.5 | $0.00003 | $0.00107 |
| Haiku 4.5 | $0.00002 | $0.00054 |
Grade A, and why
skill-installer 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 15d 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill installer
Use this skill to guide installation of another skill in the active Room Agent.
Skills are managed by the Room Agent, so these tools do not take an agentId.
Recommended workflow
- Inspect the available skills with
skills.listor read this guide withskills.read. - Start one installation with
skills.install. Always provide the targetidexplicitly. Use a structured public GitHub source when installing from a repository, or use thefilessource for URL-backed and inline files. - Treat the immediate response as an acknowledgement. Keep its
installIdand pollskills.install.get; status lookup waits up to five seconds by default and acceptswaitSecondsfrom 0 through 30. - Use
skills.install.cancelwhen queued or cancellable work should stop. Cancellation is cooperative and cannot interrupt an atomic commit. - After completion, call
skills.readto inspectSKILL.mdor a safe package-relative resource. A newly installed skill is active by default.
Replacement and retry rules
Existing skills are not replaced unless replaceExisting: true is explicit.
Replacement archives the old package under skills/.archive so it can be
restored if the commit fails. An optional Room-scoped idempotencyKey makes a
fresh retry return the original installation instead of creating a duplicate.
Only public GitHub repositories and public HTTPS file URLs are supported in
the initial version. Do not put credentials in URLs. Inline content and
contentBase64 remain available for generated files. Installation validates
the package and never executes its scripts.
Running installed scripts
For an active workspace-backed skill, skills.run accepts the skill id, a
package-relative executable path below scripts/, optional direct args, an
optional policy-validated workingDirectory, and a bounded waitSeconds.
It returns a compact managed-process observation, including the owning
agentId. Use process.read with the processId to inspect lifecycle state and
available command output, or process.cancel when execution should stop.
Command and skill output can be read in pages with process.read's cursor;
this lifecycle is separate from skills.install and its
skills.install.get / skills.install.cancel operations above.
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.
- 15d ago Changed · -1 lines 50783fc0b5f5
- 22d ago Changed · +4 lines 65003d0dc64e
- 1mo ago First seen · 51 lines · 17 tokens per session scan A 1101b3088f3f
skill-installer is a skill published in the GitHub repository slhaf/AgenticGPT (6 stars, last pushed 8d ago), licensed MIT. It adds 17 tokens to every session and 537 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
customer-journey-map
Construye un mapa de recorrido del cliente para un producto, servicio o experiencia. Úsalo cuando se te pida mapear un recorrido del cliente, crear un viaje del usuario, documentar puntos de contacto y puntos de fricción, o diseñar un mapa de experiencia. Produce un mapa de recorrido completo con etapas, puntos de…
feature-prioritisation
Aplica marcos de priorización (RICE, MoSCoW, Kano, ICE, Opportunity Scoring) para clasificar características e items del backlog. Úsalo cuando se te pida priorizar características, clasificar un backlog, decidir qué construir a continuación, o evaluar compensaciones entre ideas competidoras. Produce una lista de…
user-story-writer
Escribir historias de usuario bien estructuradas con criterios de aceptación y casos extremos. Úsalo cuando te pidan escribir historias de usuario, crear tickets a partir de un resumen de características, convertir un PRD en historias o redactar criterios de aceptación. Produce historias listas para estimar en formato…
morning-intelligence
Interviews you across 15 questions to capture your role, topics, sources, exclusions, and format preferences, then writes a master prompt you can paste into a scheduled task or Claude Code Routine. Use when you want to set up a personalised daily news brief, build a reusable morning news prompt, or create an automated…
data-analysis-standard
Estructura un análisis de datos de producto, análisis profundo de métricas, análisis de embudo o estudio de cohortes. Úsalo cuando te pidan analizar métricas de producto, investigar una caída en conversión, explicar un cambio de datos a stakeholders o encontrar la causa raíz de un movimiento de métrica. Produce un…
technical-spec-template
Crea documentos de especificación técnica estructurados que conectan requisitos de producto con implementación de ingeniería. Úsalo cuando escribas una especificación técnica, especificación de ingeniería, documento de diseño de sistema o especificación de API. Produce una especificación completa con declaración del…