research-workflow

A workflow script for a research command that divides a question into smaller questions, researches them, checks individual claims, and combines the findings.

In plain words
What is it for?
It supports multi-part web research, source checking, and evidence-based final answers when used by the research command.
Why use it?
It keeps lengthy search results and claim checks out of the main working context while leaving the research angles and final synthesis visible.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/restarter/lets-workflow/research-workflow
Any agent
npx skills add restarter/lets-workflow --skill research-workflow
Clone the repo
git clone --depth 1 https://github.com/restarter/lets-workflow

Made for: Claude Code, Codex.

Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,773 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00054 $0.01773
Opus 5 $0.00027 $0.00886
Sonnet 5 $0.00011 $0.00355
Haiku 4.5 $0.00005 $0.00177

Measured 2d ago against content hash 8eab0c788d15, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

research-workflow 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 2d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (research.workflow.js), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/lets/skills/research-workflow/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

research-workflow (Dynamic Workflow asset)

A Dynamic Workflow asset (see CLAUDE.md -> "Dynamic Workflow Assets"; review-workflow is the reference example). research.workflow.js is executed by the Workflow tool, invoked from /lets:research's Workflow Mode via:

Workflow({ scriptPath: "${CLAUDE_PLUGIN_ROOT}/skills/research-workflow/research.workflow.js", args })

${CLAUDE_PLUGIN_ROOT} is substituted at command-load time, so research.md carries the literal absolute path. Treat research.workflow.js as a template the command points at, not a script to reproduce inline.

Why this is a transparent performance lever (not autonomous)

/lets:research --workflow runs the SAME stages as the standard Task path - only the per-sub-question search dumps and per-claim verdicts stay off-context. The decompose (break the question into 3-6 sub-questions) stays IN-CONTEXT in research.md so the user can steer the angles; the per-sub-question web research and the per-claim cross-check move into the workflow (off-context); the final synthesis happens in-context after the aggregate returns. The standard path runs the equivalent stages in-context: per-sub-question research fanned out across multiple DEFAULT web Task subagents, per-claim lets:skeptic via Task. Crucially: the verify stage is a cross-check (single-source / contradicted / low-confidence flags), never a claim that the fact is confirmed correct - the skeptic has no web tools and cannot re-fetch URLs.

What it does (off-context)

  1. Research - per-sub-question fan-out via the DEFAULT web subagent (no agentType; the default workflow subagent CAN WebSearch/WebFetch - lets:* agents have tools: Read, Grep, Glob, Bash and CANNOT). Each subagent returns its 2-5 strongest claims (FINDING_SCHEMA: claim, evidence, sources, confidence) with evidence carrying QUOTED/paraphrased source material (the downstream skeptic judges "unsupported" against this string and has no web tool), and self-reports used_web_search=false rather than fabricate. mergeClaims dedupes by normalized claim text, unioning sources and keeping the highest confidence.
  2. Verify - per-claim lets:skeptic RESEARCH-VERIFY pass over the merged claims. The skeptic is handed each claim's evidence + its siblings (same sub-question) and flags STRUCTURAL weakness: unsupported (evidence does not back the claim) or contradicted (conflicts with a sibling). Single-source / low-confidence are computed deterministically by the script (those claims skip the skeptic - the deterministic flag already fires). applyVerdicts attaches a flagged[] array per claim - ADDITIVE, never drops a claim (research facts accumulate; departure from review's drop rule). Contradiction flagging is the skeptic's job comparing siblings - there is deliberately NO deterministic contradiction pass.

Read the full file on GitHub · 59 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 59 lines · 54 tokens per session scan A 8eab0c788d15

Subscribe to this mod's changes

research-workflow is a skill published in the GitHub repository restarter/lets-workflow (17 stars, last pushed 9d ago), licensed MIT. It adds 54 tokens to every session and 1,773 once invoked, about $0.0003 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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