QuickVoice: Skill for Claude Code

.claude/skills/gsd/agents/research-synthesizer/SKILL.md

gsd-research-synthesizer is a skill for Claude Code from allgpt-co/QuickVoice. It costs 37 tokens per session (1,794 once invoked), scanned A, original, MIT.

A research-summary tool that combines four separate project-research reports into one SUMMARY.md file.

In plain words
What is it for?
Use it after stack, feature, architecture, and pitfall research to inform the project's roadmap.
Why use it?
Parallel research can leave findings scattered across reports. This brings the conclusions, recommendations, uncertainties, and missing information together.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is allgpt-co/QuickVoice's own configuration. It tells Claude Code how to work on QuickVoice itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything QuickVoice configures →

Reuse

Borrowing it

Nothing to install: this file belongs to allgpt-co/QuickVoice. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/allgpt-co/QuickVoice/main/.claude/skills/gsd/agents/research-synthesizer/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/allgpt-co/QuickVoice

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,794 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00037 $0.01794
Opus 5 $0.00018 $0.00897
Sonnet 5 $0.00007 $0.00359
Haiku 4.5 $0.00004 $0.00179

Measured 11d ago against content hash 3db21c51372c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

gsd-research-synthesizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/gsd/agents/research-synthesizer/SKILL.md · 267 lines

How it starts

The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GSD Research Synthesizer

Reads outputs from 4 parallel researcher agents and synthesizes them into a cohesive SUMMARY.md.

When to Use

Use this agent when:

  • 4 parallel researcher agents have completed their research (STACK, FEATURES, ARCHITECTURE, PITFALLS)
  • You need to create a unified research summary that informs roadmap creation
  • You are spawned by /gsd:new-project orchestrator after research completes

Core Responsibilities

  1. Read all 4 research files - STACK.md, FEATURES.md, ARCHITECTURE.md, PITFALLS.md
  2. Synthesize findings - Extract key conclusions, identify patterns, derive implications
  3. Create executive summary - 2-3 paragraphs answering what type of product this is and recommended approach
  4. Extract key findings - Most important points from each research file
  5. Derive roadmap implications - Suggest phase structure, identify what needs deeper research
  6. Assess confidence - Honest evaluation of source quality
  7. Identify gaps - What couldn't be resolved and needs attention
  8. Write SUMMARY.md - Using template
  9. Commit all research - Researchers write but don't commit; you commit everything

Downstream Consumer

Your SUMMARY.md is consumed by the gsd-roadmapper agent.

How Roadmapper Uses It:

Section How Roadmapper Uses It
Executive Summary Quick understanding of domain
Key Findings Technology and feature decisions
Implications for Roadmap Phase structure suggestions
Research Flags Which phases need deeper research
Gaps to Address What to flag for validation

Be opinionated. The roadmapper needs clear recommendations, not wishy-washy summaries.

Process

Step 1: Read Research Files

Read all 4 research files:

cat .planning/research/STACK.md
cat .planning/research/FEATURES.md
cat .planning/research/ARCHITECTURE.md
cat .planning/research/PITFALLS.md

Parse each file to extract:

From STACK.md:

  • Recommended technologies with one-line rationale each
  • Any critical version requirements

Read the full file on GitHub · 267 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 267 lines · 37 tokens per session scan A 3db21c51372c

Subscribe to this mod's changes

gsd-research-synthesizer is a skill published in the GitHub repository allgpt-co/QuickVoice (489 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 1,794 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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