Results for “partial-success”

Offers fractional AI engineering and consulting services, acting as a part-time AI executive to generate $3K-10K per month.

Logs the outcome of a skill execution to observations/<skill-name>/runs.md. Trigger on: "log this run", "skill worked", "skill failed", "this didn't work", "log the outcome", "record this", "note that", or after any skill completes with a clear success, partial, or failure outcome. Creates the observations file if it does not exist, then appends an entry with date, task description, skill used, outcome, what worked, what failed, and any error messages observed.

当需要在多个领域积累独特竞争优势，避免单一技能风险时

Use this skill to evaluate which DataQ challenges have winning evidence and which don't. Covers documented vs anecdotal evidence and the 8 high-success patterns.

当遭遇挫折、失败或结果不如预期时，用于将负面经验转化为成长燃料

Result component for displaying operation results or status pages. Invoke when user needs to show success, error, warning, or HTTP status pages in Naive UI.

Drive implementation in the smallest possible meaningful increments, pausing for feedback after each step to keep work reviewable and easy to course-correct.

Graceful degradation when primary approach fails. Try alternates in priority order; record which path succeeded for future routing.

Navigate the technology adoption lifecycle from early adopters to mainstream market. Use when the user mentions "crossing the chasm", "beachhead segment", "whole product", "early adopters vs. mainstream", "tech go-to-market", "bowling pin strategy", "technology adoption lifecycle", or "pragmatist buyers". Also trigger when a startup has early traction but struggles to grow beyond initial users, or when planning go-to-market for technical products. Covers D-Day analogy, bowling-pin strategy, and positioning against incumbents. For product positioning, see obviously-awesome. For new market creation, see blue-ocean-strategy.

Benchmarks systems on the Abstraction and Reasoning Corpus (ARC) by requiring inference of abstract transformation rules from few input-output grid demonstrations and application to novel test cases, reporting the fraction of tasks solved.

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Sentinel Validation & Project Promotion

Create product objectives, key results, initiatives, guardrails, and review cadence.

Performance-coaching mode for repeated failures, passive behavior, completion-quality issues, or explicit try-harder requests. Uses structured troubleshooting and evidence-first delivery habits.

Reviews closed trades, partial exits, and monthly trade aggregates for process adherence, risk discipline, execution quality, and evidence-based trading behavior patterns.

Imported skill _template from vercel

Build a quarterly bookings forecast with commit, best-case, and pipe-only tiers, project cohort-level NRR/GRR to surface leaky cohorts, and score per-stage funnel confidence using coefficient-of-variation analysis.

Navigate the technology adoption lifecycle to cross from early adopters to mainstream markets using the D-Day strategy, beachhead selection, whole product assembly, and competitive positioning.

Read-only audit for the non-functional "20%" AI agents systematically skip: timeouts, retries with backoff+jitter, circuit breakers, idempotency keys, rate limiting, graceful. Use when "is this production-ready", "resilience audit", "will this survive real traffic", "audit retries/timeouts/idempotency", "reliability.

Autonomously repairs failed task verification by choosing retry, decompose, prune, or escalate strategies before surfacing to the user.

Execute the next incomplete step (or full phase with --phase), ship the result, and prepare the next step

Post-epic review to extract lessons and assess success. Use when the user says "run a retrospective" or "lets retro the epic [epic]"

Find the earliest decisive failure in an agent run trace and propose an evidence-backed targeted repair. Load when a run failed, results are wrong, or the user asks what went wrong in an agent session. Also triggers on "localize the fault", "first incorrect step", "debug this run", "trace attribution", "why did the agent fail", or after run-trace captures errors. Pairs with debug-and-fix for code defects and dynamic-routing for plan faults.

Skeptical pushback on visual placement — both density and quality. Reads the annotated outline plus the visuals manifest and asks (a) whether the article hits the density target from editorial-principles-visuals.md, (b) whether each [VISUAL:...] earns its place, (c) whether sections without one would benefit. One revision pass on FAIL (BLOG_AGENT_VISUALS_REVISION_BUDGET, default 1).

Audit a codebase for silent failures, swallowed exceptions, and observability gaps across Sentry and Langfuse, then produce a phased fix plan. Use when the user says "errors aren't showing in Sentry", "things fail silently", "empty catch blocks", "add error handling", "check my Langfuse tracing", or is hardening.

Read-only audit of product-analytics instrumentation: event taxonomy, funnel completeness, consent-gated firing, dead/duplicate/phantom events. Use when "audit our analytics", "are we tracking the right events", "funnel instrumentation", or before iterate-post-launch. PostHog/Amplitude/Mixpanel/GA4.

Fix failing or flaky Playwright tests. Use when user says "fix test", "flaky test", "test failing", "debug test", "test broken", "test passes sometimes", or "intermittent failure".

Facilitate a structured sprint retrospective to surface insights and produce actionable improvements with owners and deadlines.

v4.1.0 reward function redesign to fix overtrading and DSR dominance

End-of-session context handoff. Saves session state so the next session or a parallel agent can pick up exactly where the left off. Run this when context is getting full (~80%) or before stopping work.

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

Performance-coaching mode for repeated failures, passive behavior, completion-quality issues, or explicit try-harder requests. Uses structured troubleshooting and evidence-first delivery habits.

Towards Open-World Segmentation of Parts

`analysis-agent`/`task-agent`/`review-agent`: use when retryable, terminal, timeout, partial-failure, or fallback semantics change across boundaries; skip unchanged failures.

Progress component for displaying operation progress. Invoke when user needs to implement progress bars, loading indicators, or completion status in Naive UI.