Run History

Organization

runxhq

run-history

Read the workspace's runs and skill catalog, then return deterministic run outcomes, paused runs, catalog test coverage, and governance follow-ups without model-authored metrics.

Overview

Publisher	runxhq
Repository	`runx`
Skill name	`run-history`
Stars	105
Forks	109
Bundled files	6
License	Apache-2.0
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.
6 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by runxhq on GitHub. Read the source before you install it.

Installation

Install the Run History 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.
https://github.com/runxhq/runx/tree/main/skills/run-history
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/runxhq/runx.git /tmp/runx
mkdir -p .claude/skills
cp -r /tmp/runx/skills/run-history .claude/skills/run-history

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

Use it in TypingMind

Enable Run History 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 Run History 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 Run History 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.

Run History

Read the workspace's runs through the native run.list service and the installed catalog through runx.skill.inspect. The runner computes the report itself; it does not ask an agent to invent commands, launch subprocesses, or transcribe counts.

Use it for operational questions about recent Runx activity, failed or blocked runs, paused runs, frequently run skills, and skill entries without fixtures or inline harness cases. Use receipt-audit or diagnose-skill-run to inspect one suspicious run, and least-privilege when receipt-backed authority evidence is available for grant review; actual usage and policy semantics are still needed before attenuation.

Evidence boundary

Live execution reads only the native run list and catalog projections. These services read the same run records and catalog parser as the Runx CLI without routing back through the CLI as a subprocess.
Run reads are bounded to 1,000 runs.
runs and catalog_items are replay inputs for harnesses and controlled analysis, and must be supplied together; replay never silently mixes caller data with live native state.
Empty history returns needs_more_evidence rather than a healthy verdict.
completed_rate is the share of sealed runs whose outcome is completed.
refusal_rate counts sealed runs that were blocked or declined. It is reported as an observation, not automatically treated as a defect.
Catalog coverage is the number of native catalog entries declaring at least one fixture or inline harness case. It is not a maturity grade.

Output

history_report contains:

the resolved query and source labels (run.list, runx.skill.inspect, or supplied_replay);
sealed and paused run counts, outcome counts, completed/refusal rates;
the most frequently run skills;
catalog entry and test-coverage counts;
bounded recommendations routed to diagnose-skill-run, receipt-audit, or skill-build harness;
limitations when native projections cannot support a stronger claim.

This skill never executes another skill, changes a grant, or changes a run.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Run History AI skill do?

Read the workspace's runs and skill catalog, then return deterministic run outcomes, paused runs, catalog test coverage, and governance follow-ups without model-authored metrics.

Why use Run History on TypingMind?

Because you install it once and use it with any model. Run History 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 Run History in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/runxhq/runx/tree/main/skills/run-history. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Run History?

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 Run History?

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

Is the Run History AI skill free?

Yes. It is published on GitHub by runxhq under the Apache-2.0 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

Run History

Evidence boundary

Output

Bundled files

Frequently asked questions

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