CD f100k-puente
Puente para correr las skills de FÓRMULA 100K dentro de un agente OpenClaw (PapayaClaw u otro servidor). Léela SIEMPRE antes de usar cualquier skill F100K en este agente, y cada vez que una skill nombre una herramienta de Claude Code (agent-browser, claude-in-chrome, mcp__..., AskUserQuestion, subagentes, Task), una ruta de la Mac (~/Documents, ~/.claude, ~/.f100k-radar) o diga que se entregue por email. Traduce cada herramienta a su equivalente en el servidor, dice dónde se guarda cada archivo dentro del workspace, cómo leer el segundo cerebro de la usuaria y las reglas de seguridad: nada público sin ✅, todo se entrega por Telegram y nunca se entra logueada a Instagram desde el servidor.
Puente para correr las skills de FÓRMULA 100K dentro de un agente OpenClaw (PapayaClaw u otro servidor).
As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 2
✓ No critical or high findings
Medium and low: 2
-
low Exfiltration
net-credential-useSKILL.md:165Credential used in a network call (verify the destination is the intended service) (destination is a well-known publishing service; documentation of a security skill)r=urllib.request.Request('https://generativelanguage.googleapis.com/v1beta/models/gemi…ent?key='+os.environ['GEMINI_API_KEY'],known servicesecurity skill
A further 1 matches are quotations in this security skill's documentation and are not counted as findings.
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 42/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
- 70Execution cost. Instruction body is 4431 tokens
- 100Steps. 22 steps
- 100Consistency. Name and required fields are in place
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- -214 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 697: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (6 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.