Diagnose Stall

Community

danielvm-git

diagnose-stall

Diagnose why agent orchestration stopped producing progress — silent stalls in /loop, dispatch-agents, or execute-plan. Use when work appears hung, no output for several minutes, or a subagent never returned.

Overview

Publisher	danielvm-git
Repository	`bigpowers`
Skill name	`diagnose-stall`
Stars	206
Forks	18
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by danielvm-git on GitHub. Read the source before you install it.

Installation

Install the Diagnose Stall AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/danielvm-git/bigpowers.git /tmp/bigpowers
mkdir -p .claude/skills
cp -r /tmp/bigpowers/skills/diagnose-stall .claude/skills/diagnose-stall

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Diagnose Stall in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Diagnose Stall on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Diagnose Stall is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Diagnose Stall

HARD GATE — Do NOT restart work blindly. Run this diagnostic first when orchestration goes quiet without an explicit terminal state.

Explicit handler for silent stalls in long-running agent workflows (/loop, dispatch-agents, execute-plan, build-epic resume mode).

Stall signals

Signal	Likely cause
No stdout for >5 min on a monitored loop tick	Sleep/watcher misconfigured or prompt never re-armed
Subagent dispatched but no completion message	Agent hung, blocked on approval, or scope too large
`dispatch-agents` cycle 3 reached with gaps	Circuit exhausted — needs human escalation
Verify command running >15 min	Missing timeout or waiting on external service
`handoff.next_skill` unchanged across turns	Prior skill never wrote handoff

Process

Read state — specs/state.yaml: handoff.next_skill, active_flow, metrics.story_start, open decisions.
Check locks — bash scripts/check-stale-locks.sh if present; read specs/agent-locks.yaml.
Inspect terminals — list background shells; note PIDs, last output timestamp, exit codes.
Classify stall type:
- waiting_approval — tool blocked on user consent
- blocked_dependency — prior task incomplete or red gate
- agent_exhausted — max iterations/cycles reached
- misconfigured_loop — duplicate sentinel, wrong regex, or sleeper not re-armed
- external_io — network, CI, or deploy wait without timeout
- unknown — escalate with evidence bundle
Recommend recovery — one action only (resume, kill PID, re-dispatch with smaller brief, escalate to user).
Write report — specs/verifications/STALL-<timestamp>.md with classification, evidence, and recommended next skill.

Integration

Caller	When to invoke
`/loop` (Cursor)	After two consecutive ticks with no observable progress
`dispatch-agents`	When a wave exceeds expected duration with zero returns
`execute-plan`	When a step checkpoint is overdue
User	"Why did this stop?" / "Nothing is happening"

Verify

→ verify: test -f specs/state.yaml

Handoff

Gate: READY → next: survey-context (if state unclear) or resume prior skill from state.yaml Writes: specs/verifications/STALL-*.md

Frequently asked questions

What does the Diagnose Stall AI skill do?

Why use Diagnose Stall on TypingMind?

Because you install it once and use it with any model. Diagnose Stall is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Diagnose Stall in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/danielvm-git/bigpowers/tree/main/skills/diagnose-stall. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Diagnose Stall?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Diagnose Stall?

As many as you like. As long as a model supports skills, you can use Diagnose Stall with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Diagnose Stall AI skill free?

Yes. It is published on GitHub by danielvm-git under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Diagnose Stall

Stall signals

Process

Integration

Verify

Handoff

Frequently asked questions

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