Gdd Reflect

Community

hegemonart

gdd-reflect

Run design-reflector on demand - produces .design/reflections/<cycle-slug>.md with improvement proposals. Review proposals with {{command_prefix}}apply-reflections.

Overview

Publisher	hegemonart
Repository	`get-design-done`
Skill name	`gdd-reflect`
Stars	3
Forks	1
Bundled files	1
License	MIT
Links	Skill source Repository

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by hegemonart on GitHub. Read the source before you install it.

Installation

Install the Gdd Reflect 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/hegemonart/get-design-done/tree/main/scripts/skill-templates/reflect
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/hegemonart/get-design-done.git /tmp/get-design-done
mkdir -p .claude/skills
cp -r /tmp/get-design-done/scripts/skill-templates/reflect .claude/skills/gdd-reflect

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

Use it in TypingMind

Enable Gdd Reflect 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 Gdd Reflect 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 Gdd Reflect 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.

@reference/retrieval-contract.md

{{command_prefix}}reflect

Run design-reflector on demand against the current (or specified) cycle. Produces .design/reflections/<cycle-slug>.md with numbered improvement proposals. Every proposal requires explicit user review - nothing is auto-applied.

Steps

Parse args: extract --dry-run flag and --cycle <slug> value.
Resolve cycle slug:
- If --cycle <slug> given: use that slug directly
- Else: read .design/STATE.md, extract the active cycle: ID from the <position> block
- If STATE.md not found: abort with "No .design/STATE.md found. Run {{command_prefix}}new-project first."

Build required-reading list:


.design/STATE.md
.design/DESIGN-VERIFICATION.md
.design/learnings/*.md (glob)
.design/telemetry/costs.jsonl
.design/agent-metrics.json
.design/learnings/question-quality.jsonl
.design/cycles/<slug>/CYCLE-SUMMARY.md
.design/authority-report.md

Use the resolved slug where <slug> appears.

3.5. Optional: capability-gap pre-scan (Phase 29 Plan 02; runs only if .design/config.json.reflector.capability_gap_scan_enabled !== false): See @skills/reflect/procedures/capability-gap-scan.md for the full procedure. The design-reflector agent runs the scan automatically as part of its reflection pass; this step lets users dry-run it independently with:


node "${CLAUDE_PLUGIN_ROOT}/scripts/lib/reflector/capability-gap-scan.cjs" --dry-run

The scan emits capability_gap events (source: "reflector_pattern") for recurring patterns lacking a dedicated executable owner; Plan 29-03 aggregates these for {{command_prefix}}apply-reflections.

Spawn design-reflector:


Task("design-reflector", """
<required_reading>
@.design/STATE.md
@.design/DESIGN-VERIFICATION.md
@.design/agent-metrics.json
@.design/telemetry/costs.jsonl
@.design/learnings/question-quality.jsonl
</required_reading>

Cycle slug: <slug>
Dry-run: <true|false>

Produce .design/reflections/<slug>.md with all reflection sections and proposals.
If dry-run is true, print proposals to stdout only — do not write the file.
""")

After completion:

If --dry-run: print the agent output directly; skip steps below
Else: read .design/reflections/<slug>.md
Count proposals by type (scan for [FRONTMATTER], [REFERENCE], [BUDGET], [QUESTION], [GLOBAL-SKILL])

Print summary:


Reflection complete — cycle: <slug>
Proposals: N total
  [FRONTMATTER] N
  [REFERENCE] N
  [BUDGET] N
  [QUESTION] N
  [GLOBAL-SKILL] N

Review and apply: {{command_prefix}}apply-reflections

Do Not

Do not auto-apply any proposal.
Do not modify agent files, reference files, or budget.json.
Do not run the full audit pipeline - this is a standalone reflection run.
Do not bypass the threshold knob. The default reflector.capability_gap_threshold: 3 exists to suppress noise; do NOT lower it below 1.

Bundled files

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

procedures/capability-gap-scan.md7 KB

Frequently asked questions

What does the Gdd Reflect AI skill do?

Run design-reflector on demand - produces .design/reflections/<cycle-slug>.md with improvement proposals. Review proposals with {{command_prefix}}apply-reflections.

Why use Gdd Reflect on TypingMind?

Because you install it once and use it with any model. Gdd Reflect 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 Gdd Reflect in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hegemonart/get-design-done/tree/main/scripts/skill-templates/reflect. 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 Gdd Reflect?

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 Gdd Reflect?

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

Is the Gdd Reflect AI skill free?

Yes. It is published on GitHub by hegemonart 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

{{command_prefix}}reflect

Steps

Do Not

Bundled files

Frequently asked questions

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