research-sweep

research-sweep is a skill for Claude Code from alexmond/alexmskills. It costs 125 tokens per session (5,471 once invoked), scanned A, original, MIT.

A research coordinator that divides a broad question into separate areas and assigns them to parallel research agents. It combines their findings, removes duplicates, and checks the results with sources.

In plain words
What is it for?
Use it to catalog open-source projects, public datasets, or other large information spaces with independently researched and checked results.
Why use it?
It helps when you need broad, exhaustive coverage instead of a small sample of findings.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions subagents.

Part of the research-sweep plugin — 1 skill shipped together

Good fit Use it to catalog open-source projects, public datasets, or other large information spaces with independently researched and checked results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alexmond/alexmskills/research-sweep
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.

Any agent
npx skills add alexmond/alexmskills --skill research-sweep
Clone the repo
git clone --depth 1 https://github.com/alexmond/alexmskills

Made for: Claude Code.

Or install research-sweep, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for research-sweep

README.md
[![agentmods](https://agentmods.dev/badge/skills/alexmond/alexmskills/research-sweep/github.svg)](https://agentmods.dev/skills/alexmond/alexmskills/research-sweep)
Your own site
<a href="https://agentmods.dev/skills/alexmond/alexmskills/research-sweep"><img src="https://agentmods.dev/badge/skills/alexmond/alexmskills/research-sweep/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for research-sweep

Your own site · 80×15
<a href="https://agentmods.dev/skills/alexmond/alexmskills/research-sweep"><img src="https://agentmods.dev/badge/skills/alexmond/alexmskills/research-sweep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 125 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,471 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 warn 7 Sept 2026
SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Rogue Agent · line 41
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
  • medium Excessive Agency · line 258
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 $0.00125 $0.05471
Opus 5 $0.00063 $0.02736
Sonnet 5 $0.00025 $0.01094
Haiku 4.5 $0.00013 $0.00547

Measured 10d ago against content hash 91ecd51d2389, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

research-sweep 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 10d 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.

plugins/research-sweep/skills/research-sweep/SKILL.md · 276 lines

How it starts

The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Parallel research sweep

Try it: /research-sweep:research-sweep every open-source vector database — or say "give me an exhaustive catalog of public datasets for X".

This is the discover orchestrator — one of three that run on the same shared role substrate. Where dev-crew delivers a gated artifact (roles related by handoff) and brainstorm-panel decides a judgment (roles related by disagreement), the sweep discovers verified, cited findings: it composes a task-fit team of coverage roles for an information space, fans them out so each owns a disjoint angle (roles related by independence — no clash, no overlap), dedups, and adversarially verifies. The three chain — research discovers the facts, panel decides what to do, crew delivers it — and they share roles: the same skeptic is a panel seat, a crew adversarial check, and this skill's fact-verifier. (See the Role System architecture for how that shared substrate works across all three.)

For when the user wants coverage that is exhaustive, not representative. Compose the coverage roles, launch them as N parallel research agents with disjoint scopes and identical contracts, assemble their YAML/JSON outputs into one file via shell redirect — never letting the agent transcripts pass through the main context — then run an adversarial verification pass before trusting the result.

The methodology has two halves: fan-out (parallel coverage roles on disjoint slices) and verification (adversarial review of what came back). Skipping the second half produces a large but unreliable dataset.

Scope check — sweep, or a single agent?

The trigger phrases live in the description; what needs judgment once loaded is whether the ask is big enough to justify a fan-out.

Borderline asks (one agent may suffice — decide before composing a team):

  • "a list of …" with no quantity hint
  • "research X" — could be a single Explore agent

Hand the task back to a single agent if:

  • The user wants 5–20 items (single Explore or general-purpose agent is enough)
  • The domain is narrow enough that one agent can cover it well
  • The data already exists in the repo and just needs querying

Read the full file on GitHub · 276 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. 10d ago First seen · 276 lines · 125 tokens per session scan A 91ecd51d2389

Subscribe to this mod's changes

research-sweep is a skill published in the GitHub repository alexmond/alexmskills (6 stars, last pushed 2d ago), licensed MIT. It adds 125 tokens to every session and 5,471 once invoked, about $0.0006 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 2026-08-31.

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