LLM Mart Basic

Compare two versions of an LLM-directed document - an original (teacher) and a candidate (student) - across a transfer set and return a per-case behavioural-equivalence verdict plus an efficiency signal. A transform-agnostic library capability other skills compose to gate a trans

Assess a codebase's readiness for AI agent contributors using the layered contract model, and generate a complexity hotspot SVG treemap (size = LOC, hue = cyclomatic complexity, saturation = recent git churn). TRIGGER when the user types /assess, asks for an AI-readiness review,

Renders the /assess report from the deterministic run-context.json and the layer scorecard - the scorecard, the verbatim cross-layer findings, lying signals, and the mandatory Top 3 Actions. TRIGGER when the /assess orchestrator reaches the report-writing step; not a standalone u

The /assess end-of-run offers - open a PR with the report, track the Top 3 Actions in the user's issue tracker, freeze the assessment into a CI gate, and file tool feedback. TRIGGER when the /assess orchestrator reaches the end-of-run offers; not a standalone user command.

Detect and remove the telltale signs of AI-generated 'slop' from any written text - articles, reports, emails, essays, bios, marketing copy, documentation, encyclopedia entries, or anything meant to read as if a thoughtful human wrote it. Apply silently as a quality gate before f

Read-only org repo state report. Reuses ghsync's repo discovery (teams union org-repo-list) but, instead of cloning, queries each repo's remote GitHub state - open PRs, CI on the default branch, open security alerts (Dependabot / code-scanning / secret-scanning), and branch prote

Bulk clone and keep in sync every GitHub repo you can access across an org or personal account. For an org it unions the repos reachable through the teams you belong to with the org's repo list (so direct-collaborator and public repos count even with no team membership); for a pe

Structured multi-perspective analysis using Six Thinking Hats with professional lens team members. TRIGGER when the user types /huddle, asks to run a huddle, wants a panel/board/team to analyze a decision, asks for multi-perspective analysis, debate, or red-team/blue-team review,

Run a list of work units to completion with an Agent Team: derive a dependency DAG and hot-file map, spawn one ephemeral teammate per unit (or combined group), drive each PR through pr-review-merge, smart-merge in waves, recover from crashes, and run a retrospective. Source-agnos

Drive a single pull request to merge-ready across all five criteria (sync, CI, inline comments, conversation, threads), then smart-merge it. Source-agnostic library skill invoked by the /tm, /issues, /fix-pr, and /fix-develop commands and by marathon teammates. TRIGGER when a com

Make an LLM-directed document smaller while preserving what it does. Two modes: a local span-level core->pointer pass, and an A/B-validated distill loop that produces the smallest document that behaves the same as the original. Point at core knowledge the model already holds (a c

Phase-1 (S4) of a comic movie — PRODUCE the canonical reusable references the whole spiral conditions on. Per asset it bakes ONE canonical 1:1 white-bg identity ref via the agent mcp__codex__codex sidecar bake (Codex native image_gen — conditioned, never hand-pasted) OR, for a de

Phase-1 (S5) UPSTREAM ref-asset gate — the bounded cross-model adversarial loop that LOCKS one reusable identity-locked asset (character sheet / location plate / prop cutout / text-panel / logo-free symbol) BEFORE it can be composited into any panel. This is NOT the panel_gate (c

Phase 1 ORCHESTRATOR of a movie/comic — turn a fuzzy story idea into the Authored Source of Truth (a schema-valid comic.json + its locked asset library) by driving the detailed author skills in order (intent → style → outline → storyboard → assets → blueprints → prompts → comic.j

Phase-1 comic-author step (post-final eval) — a DOUBLE-BLIND A/B of two FINAL whole comics: our cross-model-audited progressive render (the comic-author + comic-director output) vs a naive single-shot baseline. A single sealed coin-flip hides which is which; two cross-model revie

Phase-1 (S7 of the comic-author suite) — turn ONE locked panel_spec into a deterministic content-SVG blueprint that becomes the bake condition (reference #1 of the agent mcp__codex__codex sidecar bake), by WRITING A PYTHON GENERATOR (never raw SVG in chat — LLMs botch coordinates

The authoring-side DIEGETIC continuity AUDIT — it produces the world-state evidence that comic-cross-layer-gate `--gate continuity` adjudicates against the storyboard's MOTIF STATE TABLE (motif_ledger). It checks each baked panel STRICTLY against the pre-committed table row, then

The ONE parameterized score-fuser for EVERY comic-author authoring gate — `--gate intent|outline|asset|storyboard|blueprint|continuity|p0_proof|compile`. A single fuser (not a per-layer split) prevents drift. It NEVER re-runs a reviewer; it collects the reviewer score-nodes alrea

Phase 2/3 of a movie — bake + cross-model-verify a movie from an authored comic.json. Per frame: render the content-SVG blueprint, bake via the agent mcp__codex__codex sidecar, gate with a 3-reviewer cross-model panel (narrative [currently the codex CLI] ‖ Gemini visual ‖ Codex v

Phase-1 Layer-0 of the comic-author suite — turn ANY raw idea / a locked video skeleton / an audience note into ONE schema-valid intent_spec node that fixes the logline (an editorial climax), the tagline, and the named DUAL-IDENTITY design constraint the whole comic optimizes aga

Fourteen posts of being wrong in production, compressed to checkboxes

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

Update implementation documentation including specs, status, and best practices

Use structured stepper approach for problem-solving and project development

Write unit and integration tests

Developer agent — implements features based on technical design, follows TDD patterns, and produces clean, tested code

Autonomous iteration loop — reads progress, selects role, executes, verifies, commits, and moves to next task without waiting

Pair programming mode — step-by-step collaboration with 5 confirmation checkpoints for learning and sensitive operations

Product Manager agent — analyzes requirements, creates REQ documents, and breaks down features into actionable items

Configure claude-hud as your Claude Code statusline

Grade this repo's CLAUDE.md / AGENTS.md (0–100) and return a worst-first fix list

Scaffold a CLAUDE.md for this repo from battle-tested templates, filled in with the project's real commands

Prompt optimizer — rewrite this request into an optimized prompt (ultrathink), then carry it out

Configure codex-hud statusline display options (guided interactive flow)

Show last 30 days Codex cost breakdown

Show today's Codex cost breakdown

Show last 7 days Codex cost breakdown

Configure or update the OpenAI Admin API key (enables /codex-hud:costs-*)

Install codex-hud statusline (automatic, idempotent)

Quick one-line summary of today's Codex activity (cost shown if Admin key configured)

Remove the codex-hud statusline integration (restores your previous statusline)

Показать состояние гейта качества 1С — какие файлы ждут проверки

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AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

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一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

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