rapid-research
- Repo stars 3
- Author updated Live
- Author repo FFT_nano
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @0-CYBERDYNE-SYSTEMS-0 · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Required · Vendor-specific
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- External requests
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: rapid-research
description: Lightweight research playbook optimized for the FF-Terminal agent. Use when another skill is a b…
category: ai
runtime: no special runtime
---
# rapid-research output preview
## PART A: Task fit
- Use case: Lightweight research playbook optimized for the FF-Terminal agent. Use when another skill is a better direct match for the task. | Source | Date | Key Fact | Link | Confidence | requires Vendor-specific API key. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When not to use this skill / When to use it / Guardrails” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Lightweight research playbook optimized for the FF-Terminal agent. Use when another skill is a better direct match for the task. | Source | Date | Key Fact | Link | Confidence | requires Vendor-specific API key. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “When not to use this skill / When to use it / Guardrails” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; may access external network resources; requires Vendor-specific API keys.
## Running Rules
- read files, write/modify files, run shell commands; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. Choose the trigger
The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Provide inputs and boundaries
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Validate with a small run
Start with a small task and check whether the result follows “When not to use this skill / When to use it / Guardrails”. Inspect diffs, logs, previews, or tests before expanding scope.
Review before delivery
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: rapid-research
description: Lightweight research playbook optimized for the FF-Terminal agent. Use when another skill is a b…
category: ai
source: 0-CYBERDYNE-SYSTEMS-0/FFT_nano
---
# rapid-research
## When to use
- Lightweight research playbook optimized for the FF-Terminal agent. Use when another skill is a better direct match for…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “When not to use this skill / When to use it / Guardrails” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. Evidence boundary and execution chain
The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "rapid-research" {
input -> user goal + target files + boundaries + acceptance criteria
context -> When not to use this skill / When to use it / Guardrails
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | may access external network resources
guardrails -> requires Vendor-specific API keys + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}Rapid Research Loop
When not to use this skill
- Do not use when another skill is a better direct match for the task.
- Do not use when the request is outside this skill's scope.
When to use it
- The user needs a structured briefing, comparison table, FAQ, or short memo derived from multiple sources.
- The task explicitly says "research", "investigate", "summarize", or requests citations/links.
- Another agent already gathered raw notes and you must distill them.
Guardrails
- Always collect at least three independent sources unless the user provided authoritative material.
- Keep a running source log (see
templates/source_log_template.md) before drafting a summary. - Mark uncertainty or missing data instead of fabricating details.
- Prefer deterministic helper scripts for parsing (CSV/JSON) before reasoning about them.
Step-by-step workflow
- Clarify the question – restate the core decision or comparison criteria in one paragraph.
- Plan the evidence sprint – list the minimum facts you must confirm; group them by sub-question.
- Collect evidence – for each fact, gather a citation with date, outlet, and a one-sentence pull quote.
- Grade sources – label each entry with
primary,secondary, orspeculative. - Synthesize – transform the evidence table into:
- a 3-bullet executive summary,
- a risk/unknowns list,
- and next-step recommendations.
- Package output – use
templates/research_brief_template.mdas the outline and include the source log verbatim at the end.
Output template
## TL;DR (3 bullets)
- ...
## Key Findings
1. Finding + cite
2. ...
## Risks / Unknowns
- ...
## Next Best Actions
- ...
## Source Log
| Source | Date | Key Fact | Link | Confidence |
| --- | --- | --- | --- | --- |Web Search with ddgs
Use ddgs (DuckDuckGo) for free, no-API-key web search. Available as CLI:
ddgs text -q "search query" -m 5 # text search, 5 results
ddgs news -q "search query" -m 5 # news search
ddgs images -q "search query" -m 5 # image searchExample research workflow:
# Search for evidence
ddgs text -q "OpenAI GPT-5 release date" -m 3
ddgs text -q "Claude 4 release date" -m 3
# Extract key facts from results
# (results include title, href, body/snippet)ddgs is pre-installed in the pi container runtime. Use bash to invoke it.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review