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cccskills

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300 件(pjt222 のリポジトリ) ・ 人気順

概要と使いどころ

Evolve SKILL.md files from agent execution traces using a three-stage pipeline: trajectory collection from observed runs, parallel multi-agent patch proposal for error and success analysis, and conflict-free consolidation of overlapping edits via prevalence-weighting. Based on the Trace2Skill methodology.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Evolve an existing skill by refining its content in-place or creating an advanced variant. Covers assessing the current skill, gathering evolution requirements, choosing scope (refinement vs. variant), applying changes, updating version metadata, and synchronizing the registry and cross-references. Use when a skill's procedure steps are outdated, user feedback reveals gaps, a skill needs a complexity upgrade, an advanced variant is needed alongside the original, or related skills are added and cross-references are stale.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Evolve an existing team composition by refining its structure in-place or creating a specialized variant. Covers assessing the current team against template and coordination patterns, gathering evolution requirements, choosing scope (adjust members, change coordination pattern, split/merge teams), applying changes to the team file and CONFIG block, updating version metadata, and synchronizing the registry and cross-references. Use when a team's member roster is outdated, coordination pattern no longer fits, user feedback reveals workflow gaps, a specialized variant is needed alongside the original, or agents have been added or removed from the library affecting team composition.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Structured procedure for expanding attention from focused single-domain mode to panoramic multi-domain awareness. The cognitive transition from "focused attention on one problem" to "unfocused attention encompassing all relevant domains simultaneously." Like Baars' Global Workspace — consciousness as broadcast rather than spotlight. Use after meditation has cleared noise, when a problem spans multiple domains that need to be perceived together, when single-domain analysis keeps missing cross-domain connections, or as the opening move before integrate-gestalt synthesizes what is perceived.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Solve Diophantine equations (integer-only solutions) including linear, quadratic, and Pell equations. Covers the extended Euclidean algorithm, descent methods, and existence proofs. Use when finding all integer solutions to ax + by = c, solving Pell's equation, generating Pythagorean triples, proving no integer solutions exist via modular constraints, or finding the fundamental solution from which all others are generated.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Communicate an integrated insight in a way that is accessible, actionable, and preserves the multi-domain nature of the understanding. Integrated insights are multi-dimensional — linearizing them risks losing the relationships that make them valuable. This skill provides a structured procedure for choosing the right form, expressing the gestalt with honest attribution, and inviting productive challenge. Use after integrate-gestalt has formed a cross-domain understanding that needs to be communicated to an audience — domain specialists, generalists, or decision-makers.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Apply the fail-early (fail-fast) pattern to detect and report errors at the earliest possible point. Covers input validation with guard clauses, meaningful error messages, assertion functions, and anti-patterns that silently swallow failures. Primary examples in R with general/polyglot guidance. Use when writing functions that accept external input, adding input validation before CRAN submission, refactoring code that silently produces wrong results, reviewing PRs for error-handling quality, or hardening internal APIs against invalid arguments.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Trademark filing procedures covering EUIPO (EU), USPTO (US), and WIPO Madrid Protocol (international). Walks through pre-filing conflict checks, Nice classification, descriptiveness assessment, mark type decisions, filing basis strategy, office-specific e-filing procedures, Madrid Protocol extension, post- filing monitoring, and open-source trademark policy drafting. Use after running screen-trademark to confirm the mark is clear, when ready to secure trademark rights in one or more jurisdictions.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Create R-based pictogram glyphs for skill, agent, or team icons in the visualization layer. Covers concept sketching, ggplot2 layer composition using the primitives library, color strategy, registration in the appropriate glyph mapping file and manifest, rendering via the build pipeline, and visual verification of the neon-glow output. Use when a new entity has been added and needs a visual icon for the force-graph visualization, an existing glyph needs replacement, or when batch-creating glyphs for a new domain.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Create a GitHub release with proper tagging, release notes, and optional build artifacts. Covers semantic versioning, changelog generation, and GitHub CLI usage. Use when marking a stable version of software for distribution, publishing a new library or application version, creating release notes for stakeholders, or distributing build artifacts (binaries, tarballs).

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Structured GitHub issue creation from review findings or task breakdowns. Groups related findings into logical issues, applies labels, and produces issues with standard templates including summary, findings, and acceptance criteria. Designed to consume output from review-codebase or similar review skills.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Create general-purpose Dockerfiles for Node.js, Python, Go, Rust, and Java projects. Covers base image selection, dependency installation, user permissions, COPY patterns, ENTRYPOINT vs CMD, and .dockerignore. Use when containerizing an application for the first time, creating a consistent build/runtime environment, preparing an app for cloud deployment or Docker Compose, or when no existing Dockerfile is present in the project.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Set up a Blender scene programmatically via Python (bpy) with objects, materials, lighting, camera, and environment configuration. Use when creating reproducible 3D visualization scenes, automating product or architectural rendering setup, generating multiple scene variations programmatically, building template scenes for batch rendering workflows, or integrating 3D visualization into data pipelines.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Compose 2D graphics programmatically using SVG generation, diagram layout algorithms, image compositing, and batch processing workflows. Use when generating diagrams, flowcharts, or infographics programmatically, creating reproducible scientific figures, automating production of badges or visual assets, building custom chart types not in standard libraries, or batch generating graphics with parameter variations.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Unify metrics, logs, and traces for cohesive debugging. Implement exemplars for log-to-trace linking, build unified dashboards using RED/USE methods, and enable rapid root cause analysis across observability signals. Use when investigating complex incidents spanning multiple systems, reducing mean time to resolution, implementing distributed tracing, or moving from siloed tools to a unified observability platform.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

AI internal coordination using stigmergic signals — managing information freshness in context and memory, decay rates for assumption staleness, and emergent coherent behavior from simple local protocols. Use during complex tasks where multiple sub-tasks must coordinate, when context has grown long and information freshness is uncertain, after context compression when information may have been lost, or when sub-task outputs need to feed into each other cleanly without degradation.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Coordinate safely with a peer interactive session sharing the same git worktree — check first whether a separate worktree removes the problem, then declare path and branch scope before the first edit, survive a contended index lock, and review the whole branch before opening a PR. Activate when starting work in a repository that may already be occupied, when a git command fails with `index.lock: File exists`, when `guard:snapshot` refuses because a snapshot already exists, or when a commit turns out to contain a file this session never edited. When one session leads and the other supports, divide the labour by shape and re-derive every reported number against a named revision before citing it. Distinct from subagent concurrency: a peer session cannot be bracketed, because no baseline exists from before its edits.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Containerize an R-based MCP (Model Context Protocol) server using Docker. Covers mcptools integration, port exposure, stdio vs HTTP transport, and connecting Claude Code to the containerized server. Use when deploying an R MCP server without requiring a local R installation, creating a reproducible MCP server environment, running MCP servers alongside other containerized services, or distributing an MCP server to other developers.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Reference Hildegard von Bingen's Physica natural history knowledge. Covers classification of plants, stones, animals, fish, birds, elements, and trees with their medicinal, symbolic, and practical properties. Enables cross- referencing between categories and application guidance. Use when exploring a specific plant, stone, or animal from Hildegard's perspective, researching medieval natural history and cosmology, cross-referencing properties across categories, or integrating Physica knowledge into health, spiritual, or creative practice.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Add an external probabilistic classifier to a decision path without letting it take the path over. Covers finding the externally-graded rows you are already logging, measuring the confidence separation between the overrides it got right and the ones it got wrong, choosing an operating point your data licenses, failing open at the call site, and proving the whole arrangement offline with no API key. Applies to any service returning a score you can order — TypeSafe AI's System One models (Jev) are the worked example. Most of the method transfers to a local model or a second heuristic, with the parts that do not called out where they arise. Use when a rule-based path is wrong often enough to hurt, when someone proposes replacing a heuristic with a model, when a confidence threshold needs a defensible value, or when an oracle already in production has never been graded.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Perform a ruler-and-compass construction with step-by-step justification for each operation, producing a constructible geometric figure from given elements. Covers classical Euclidean constructions including perpendicular bisectors, angle bisectors, parallel lines, regular polygons, and tangent lines. Use when given geometric elements (points, segments, angles) and asked to produce a Euclidean construction, verify constructibility, or generate ordered construction steps for educational or documentation purposes.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Thoroughness and diligence in execution — systematic checking, completeness verification, follow-through on commitments, and the discipline of finishing well. Maps the personality trait of conscientiousness to AI task execution: not cutting corners, verifying results, and ensuring that what was promised is what was delivered. Use before marking a task as complete, when a response feels "good enough" but deserves better, after a complex multi-step operation where steps may have drifted, or when self-monitoring detects a pattern of cutting corners or rushing.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新

Configure the putior MCP server to expose 16 workflow visualization tools to AI assistants. Covers Claude Code and Claude Desktop setup, dependency installation (mcptools, ellmer), tool verification, and optional ACP server configuration for agent-to-agent communication. Use when enabling AI assistants to annotate and visualize workflows interactively, setting up a new development environment with putior MCP integration, or configuring agent-to-agent communication via ACP for automated pipelines.

日本語の概要は準備中です。原文の説明を表示しています。

pjt222/agent-almanac372026年10月12日 更新