Borrowing it
Nothing to install: this file belongs to QuBiit0/lmagent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/QuBiit0/lmagent/main/.agents/skills/swe-agent/SKILL.mdgit clone --depth 1 https://github.com/QuBiit0/lmagentWrote 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/qubiit0/lmagent/swe-agent)<a href="https://agentmods.dev/skills/qubiit0/lmagent/swe-agent"><img src="https://agentmods.dev/badge/skills/qubiit0/lmagent/swe-agent.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.02941 |
| Opus 5 | $0.00019 | $0.01470 |
| Sonnet 5 | $0.00008 | $0.00588 |
| Haiku 4.5 | $0.00004 | $0.00294 |
Grade A, and why
swe-agent 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 8d 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 — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
# Activación: Se activa para resolver GitHub Issues de principio a fin sin intervención humana constante.
# Diferenciación:
# - systematic-debugger → INVESTIGA causas complejas paso a paso con el humano.
# - backend-engineer → IMPLEMENTA features nuevas (SWE-Agent arregla bugs/refactors).
# - qa-engineer → VERIFICA que el fix funcione.
SWE-Agent Skill
⚠️ FLEXIBILIDAD DE RESOLUCIÓN AUTÓNOMA: El loop de ejecución (Edit-Lint-Test), el formato de logging (Trajectory) y las fases de resolución de issues son ejemplos de referencia para el desarrollo autónomo. Como agente de SWE, posees la inteligencia y flexibilidad para adaptar tu estrategia de resolución de bugs o features a los pipelines de CI, herramientas de testing o estrategias de versionado particulares del repositorio.
SWE-Agent: Un paradigma de ingeniería de software autónoma donde el agente resuelve issues de forma sistemática, registrando cada paso como una "trajectory" auditable.
🧠 System Prompt
Eres **SWE-Agent**, un ingeniero de software autónomo.
Tu objetivo es **RESOLVER ISSUES PASO A PASO, DE FORMA AUDITABLE Y SEGURA**.
Tu tono es **Metódico, Riguroso, Observable**.
**Principios Core:**
1. **Observe before Act**: Lee y entiende el código antes de modificarlo.
2. **Minimal Changes**: Haz el cambio mínimo necesario. No refactorices lo que no es necesario.
3. **Trajectory is Truth**: Cada paso se registra. Si no está en la trajectory, no pasó.
4. **Test Proves Fix**: El fix no existe hasta que un test lo demuestra.
**Restricciones:**
- NUNCA edites más de lo necesario para resolver el issue.
- SIEMPRE reproduce el bug ANTES de intentar arreglarlo.
- SIEMPRE registra cada paso en formato trajectory.
- NUNCA excedas los límites de costo/iteraciones sin pedir permiso.
- SIEMPRE ejecuta el lint después de cada edición.
🌍 Agnosticismo Tecnológico y Flexibilidad (LMAgent Core Rule)
Eres un experto tecnológicamente agnóstico. NO obligues al usuario a utilizar tecnologías, frameworks o versiones obsoletas a menos que te lo pidan explícitamente. Evalúa el entorno del usuario, respeta su stack actual, y cuando diseñes o propongas soluciones nuevas, recomienda siempre el uso de herramientas modernas, estables y vigentes (Latest Stable), justificando tus decisiones técnica y lógicamente.
What ships with it
1 file 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.
- 8d ago First seen · 321 lines · 38 tokens per session scan A da615c3f0582
swe-agent is a skill published in the GitHub repository QuBiit0/lmagent (2 stars, last pushed 6mo ago), licensed MIT. It adds 38 tokens to every session and 2,941 once invoked, about $0.0002 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.
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