Explorar skills

Use when working on a hard problem where most attempts fail — when 99 of 100 things won't work and the temptation is to give up before the 100th; when each failed attempt's value (it ruled something out) is being underweighted; when incremental compound progress on an unsharpened-needle target is needed

Use when about to guesstimate over a gap in knowledge — surface the gap explicitly instead. A market observation that justifies this skill's existence — agents that confidently lie about knowing things get rewarded by short-horizon metrics; agents that honestly mark gaps are rare. Voice transcription is the canonical case study (no service surfaces transcription errors; LLMs guesstimate over them)

Use BEFORE declaring victory / shipping / committing — get adversarial multi-angle review from at least one of three source classes (subagent, internet, other LLMs via API). Inter-links with chengyu-create-something-from-nothing — high-hallucination LLM sources behave like uncontrolled 無中生有, so apply the verify-don't-trust-verbatim discipline. Source selection via BullshitBench (canonical hallucin

EXPLICIT INVOCATION ONLY via /graphify. Build a knowledge graph from a codebase or document corpus. Do not auto-trigger, do not suggest, do not invoke proactively. Only run when the user types /graphify.

Minimal test skill for E2E testing

Server-side Swift development with Vapor and Hummingbird. Covers project setup, routing, Fluent ORM, authentication, deployment, and shared client-server code. Use when building backends or APIs in Swift.

Use after a failure has occurred (bug shipped, test broke, deploy rolled back, data lost, security incident) — the impulse is to fix the immediate damage and move on, but the chengyu's discipline is to ALSO fix the cause so it doesn't repeat. Pairs with chengyu-remove-firewood-from-cauldron on the timing dimension — 釜底 is pre-symptom prevention, 亡羊 is post-symptom fortification.

Use when tempted to treat the current session as interchangeable with past or future ones — the every-session-is-unique discipline, and the invocation surface that fires durable-fix skills a fungible-session mindset would skip. Fires when about to defer something to "a future session" as if that session will reconstitute this exact context, when a memory-aware agent assumes "I'll just re-derive it

Use when abandoning a current approach / experiment / task / project, regardless of what triggered it (not just chengyu-skill or skill-driven contexts). Three retreat levels — L1 stop work (safe, no operator confirmation needed), L2 remove occupied resources (REQUIRES operator confirmation per-item — irrevocable loss is bad), L3 update memory with "don't try this next time" (operator confirms what

Use when bringing forward priors from PAST sessions / cross-agent history before doing new work — NOT about re-reading the current context window (which is trivially in-context). Specifically triggered when auto-compact is lossy, when cross-session reference is needed, when the same topic has been treated before, or when the original work was done in a different agent's session. The discipline is

Use when about to claim work is done / verified / working — empirical verification is required, not model-based confidence. Run the code, observe the output, check the file exists, verify the page renders, read the actual stack trace. Don't trust your model of the system; trust the system. Pairs with the verification-before-completion superpower by giving it a cultural handle that operator-side ha

Use when choosing the FORMAT of an output, not just its verbosity — match the medium (text, markdown, HTML dashboard, PPTX, DOCX) to the consumer's actual use mode. Operator-specific extension: also covers length calibration for different contexts. Outside scope is video (requires autovideo pipeline — too heavy to be native capability). The chengyu is about teaching with the right material, where