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 contactandrewchl-wq/turtle-mcp --skill reporte-comprensiblegit clone --depth 1 https://github.com/contactandrewchl-wq/turtle-mcpWrote 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/contactandrewchl-wq/turtle-mcp/reporte-comprensible)<a href="https://agentmods.dev/skills/contactandrewchl-wq/turtle-mcp/reporte-comprensible"><img src="https://agentmods.dev/badge/skills/contactandrewchl-wq/turtle-mcp/reporte-comprensible/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/contactandrewchl-wq/turtle-mcp/reporte-comprensible"><img src="https://agentmods.dev/badge/skills/contactandrewchl-wq/turtle-mcp/reporte-comprensible.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 | $0.00090 | $0.00559 |
| Opus 5 | $0.00045 | $0.00280 |
| Sonnet 5 | $0.00018 | $0.00112 |
| Haiku 4.5 | $0.00009 | $0.00056 |
Grade A, and why
reporte-comprensible 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 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.
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.
What it actually says
Reporte comprensible — que la persona entienda lo que recibió
La primera frase
La primera frase de todo reporte responde "¿qué pasó?" en lenguaje llano, sin jerga:
"Ya funciona el ingreso con Google; probé el flujo completo y quedó listo para usar."
NO empieces por el proceso ("primero revisé…, después edité…"): eso va después, para quien quiera el detalle.
La estructura
- Resultado — qué cambió para la persona, en una o dos frases llanas.
- Cómo probarlo — pasos concretos y copiables (comandos, URLs, qué debería ver). Si no se puede probar a mano, di cómo se verificó.
- Decisiones y supuestos — qué decidiste por tu cuenta y por qué, para que pueda vetarlo.
- Riesgos y pendientes — en términos de impacto ("si pasa X, el efecto es Y"), no de tecnología.
La jerga
Cada término técnico que la persona no haya usado antes se explica entre paréntesis la primera vez:
"Agregué un índice FTS (el mecanismo que hace rápida la búsqueda por palabras)…"
Si el proyecto tiene glosario (glosario-vivo), usa los términos del glosario tal como están definidos.
La honestidad
- Si algo falló, dilo en la primera frase, no en el pie de página.
- Si un test no pasa o algo quedó a medias, se reporta como está: nunca "listo" con asterisco escondido.
- Distingue "lo verifiqué" (con evidencia) de "debería funcionar" (sin evidencia). La persona decide distinto según cuál sea.
El tamaño
El reporte se lee en menos de un minuto. El detalle extenso (diffs, logs, tablas) va después del resumen o en la memoria de Turtle (memory_save), no en el medio del mensaje.
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 · 42 lines · 90 tokens per session scan A d09801cd1e71
reporte-comprensible is a skill published in the GitHub repository contactandrewchl-wq/turtle-mcp (2 stars, last pushed 2mo ago), licensed MIT. It adds 90 tokens to every session and 559 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
gno
Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs…
engram-memory
Give the agent durable, local memory with engram — recall past decisions before answering, and persist new decisions, preferences and facts as they happen. Use when work spans sessions or the user says "remember".
simplicio-loop
Unified public entrypoint for Simplicio's body-of-work orchestration: core + loop in one command. Use when the user types /simplicio-loop, says "ralph loop", "keep iterating until done", "finish all open issues", or asks to drain a queue of work autonomously. Runtime-agnostic: binds a real stop-hook where the host…
simplicio-nest-gate
N-Nest protocol — multi-level gate-corrected agent tree. PRIME depth verification, BH port.port.port addressing, per-level confabulation catch.
simplicio-orient
Terminal-first execution — answer facts with the shell, never with the LLM. Use whenever a step needs a fact about the filesystem, git, processes, or system resources, or runs a build/test/lint/diff whose output would flood context. Substitutes deterministic shell/CLI calls for native LLM operations and clamps their…
simplicio-autoresearch
Evolutionary optimize-by-metric loop — mutate a target, evaluate against fixed criteria, KEEP if the score improves (commit) or REVERT if it doesn't (git checkout), repeat, plateau-break after N stagnated runs. Adapts Karpathy's autoresearch pattern (and the ECC autoresearch-agent) with mandatory yool guardrails (§11…