Ghm Harvest logo

Ghm Harvest

Community
mattgierhart
ghm-harvest

Extracts durable insights from temp/ files to SoT during EPIC Phase E. Triggers at EPIC completion or explicit `/ghm-harvest` invocation. Outputs new SoT entries and archive manifest.

Overview

Publishermattgierhart
RepositoryPRD-driven-context-engineering
Skill nameghm-harvest
Stars
179
Forks
11
Bundled files
3
LicenseMIT
Links
  • 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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mattgierhart on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/mattgierhart/PRD-driven-context-engineering.git /tmp/PRD-driven-context-engineering
mkdir -p .claude/skills
cp -r /tmp/PRD-driven-context-engineering/plugins/prd-ce/skills/ghm-harvest .claude/skills/ghm-harvest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ghm Harvest 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 Ghm Harvest 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 Ghm Harvest 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.

Harvest

Extract durable insights from temporary files to Source of Truth during EPIC Phase E (Finish).

Workflow Overview

  1. Enumerate Temps → List all temp/ files from current EPIC
  2. Identify SoT-worthy → Determine what should persist
  3. Format Entries → Convert to proper SoT templates
  4. Archive → Move temps to archive, update manifest

Core Output Template

ElementDefinitionEvidence
Temp FilesFiles processedList with paths
New SoT EntriesIDs createdBR-XXX, UJ-XXX, etc.
Archive ManifestWhat was archivedPaths and dates
DiscardedWhat was not keptReason for each

Harvest Decision Matrix

Content TypeActionDestination
Business rule discoveredExtractSoT/SoT.BUSINESS_RULES.md
User flow documentedExtractSoT/SoT.USER_JOURNEYS.md
API design finalizedExtractSoT/SoT.API_CONTRACTS.md
Customer feedback capturedExtractSoT/SoT.customer_feedback.md
Session notesArchive onlyarchive/YYYY-MM/
Scratch workDiscardDelete after review

Step 1: Enumerate Temp Files

  1. Read EPIC Execution Plan for temp file references
  2. List all files in temp/ directory
  3. Match temps to EPIC (by date or naming)

Checklist

  • All EPIC-referenced temps identified
  • Temp directory scanned
  • Files categorized by content type

Step 2: Identify SoT-Worthy Content

For each temp file, evaluate:

QuestionIf YesIf No
Is this a business rule?Extract as BR-XXXContinue
Is this a user flow?Extract as UJ-XXXContinue
Is this an API design?Extract as API-XXXContinue
Is this customer evidence?Extract as CFD-XXXContinue
Is this useful context?ArchiveContinue
Is this scratch work?Discard-

Checklist

  • Each temp file evaluated
  • Extract/Archive/Discard decision made
  • Decisions documented

Step 3: Format SoT Entries

For each extracted item:

  1. Generate appropriate ID using ghm-id-register
  2. Format per SoT template
  3. Add cross-references
  4. Insert into correct SoT file

Entry Template

markdown
### [ID]: [Title]

**Status**: Active
**Created**: YYYY-MM-DD
**Source**: temp/[filename].md (EPIC-XX)
**Cross-References**: [Related IDs]

[Extracted content, properly formatted]

Checklist

  • All extracts have valid IDs
  • Formatting matches SoT templates
  • Cross-references verified

Step 4: Archive and Cleanup

  1. Create archive directory: archive/YYYY-MM/
  2. Move processed temps to archive
  3. Generate manifest
  4. Update EPIC Phase E checklist

Archive Manifest Template

markdown
## Archive Manifest: EPIC-XX

**Date**: YYYY-MM-DD
**Archived To**: archive/YYYY-MM/

### Extracted to SoT
| Temp File | New ID | SoT File |
|-----------|--------|----------|
| temp/file.md | BR-XXX | SoT.BUSINESS_RULES.md |

### Archived Only
| Temp File | Reason |
|-----------|--------|
| temp/notes.md | Session context |

### Discarded
| Temp File | Reason |
|-----------|--------|
| temp/scratch.md | No durable value |

Quality Gates

Pass Checklist

  • All temps processed (none orphaned)
  • Extracted content has valid IDs
  • Archive manifest is complete
  • EPIC Phase E checklist updated

Testability Check

  • SoT entries are findable by ID
  • Archive manifest matches actual files
  • Temp directory is clean

Anti-Patterns

PatternExampleFix
Orphan tempsTemps not in manifest→ Process all files
Lost contextArchive without manifest→ Always create manifest
Over-extractionEverything becomes SoT→ Apply decision matrix
Under-extractionValuable insights lost→ Review before discard

Boundaries

DO:

  • Extract durable insights
  • Format per templates
  • Create complete manifests
  • Clean up temps

DON'T:

  • Create new analysis
  • Modify conclusions
  • Skip the manifest
  • Delete without review

Handoff

After harvest completes:

  • SoT files updated with new entries
  • Temps archived with manifest
  • EPIC Phase E marked complete
  • Ready to close EPIC

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 Ghm Harvest AI skill do?

Extracts durable insights from temp/ files to SoT during EPIC Phase E. Triggers at EPIC completion or explicit `/ghm-harvest` invocation. Outputs new SoT entries and archive manifest.

Why use Ghm Harvest on TypingMind?

Because you install it once and use it with any model. Ghm Harvest 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 Ghm Harvest in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mattgierhart/PRD-driven-context-engineering/tree/main/plugins/prd-ce/skills/ghm-harvest. 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 Ghm Harvest?

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 Ghm Harvest?

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

Is the Ghm Harvest AI skill free?

Yes. It is published on GitHub by mattgierhart 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇