deep-research

deep-research is a skill for Claude Code from Samuel0101010/wisp-orchestrator. It costs 28 tokens per session (165 once invoked), scanned A, original, Apache-2.0.

A focused research workflow that examines project files, searches available knowledge, optionally reads up to three external sources, and produces a structured report.

In plain words
What is it for?
Use it to investigate a codebase or technical topic, locate relevant files, consult a small number of outside sources, and summarize what is known.
Why use it?
It gathers evidence in one place instead of relying on assumptions or scattered notes. The report separates the summary, findings with file references, and unresolved questions.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Part of the wisp plugin — 12 skills, 1 command, 4 agents, 6 hooks shipped together

Good fit Use it to investigate a codebase or technical topic, locate relevant files, consult a small number of outside sources, and summarize what is known.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/samuel0101010/wisp-orchestrator/deep-research
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 Samuel0101010/wisp-orchestrator --skill deep-research
Clone the repo
git clone --depth 1 https://github.com/Samuel0101010/wisp-orchestrator

Made for: Claude Code.

Or install wisp, the plugin that ships this one along with the rest of its 12 skills, 1 command, 4 agents, 6 hooks.

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 deep-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/samuel0101010/wisp-orchestrator/deep-research/github.svg)](https://agentmods.dev/skills/samuel0101010/wisp-orchestrator/deep-research)
Your own site
<a href="https://agentmods.dev/skills/samuel0101010/wisp-orchestrator/deep-research"><img src="https://agentmods.dev/badge/skills/samuel0101010/wisp-orchestrator/deep-research/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 deep-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/samuel0101010/wisp-orchestrator/deep-research"><img src="https://agentmods.dev/badge/skills/samuel0101010/wisp-orchestrator/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 165 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.
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 $0.00028 $0.00165
Opus 5 $0.00014 $0.00082
Sonnet 5 $0.00006 $0.00033
Haiku 4.5 $0.00003 $0.00016

Measured 9d ago against content hash 3ea9d252d89a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

deep-research 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 9d 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.

apps/dashboard-server/src/skills/seed/deep-research/SKILL.md · 18 lines

What it actually says

You are a research specialist. Given the topic in the user message:

  1. Explore the codebase via Read/Grep/Glob to gather concrete file references
  2. If WebFetch is available, fetch up to 3 relevant external sources
  3. Synthesize findings into:
    • Summary (3 sentences)
    • Key findings (bullets, each with file:line citation)
    • Open questions (bullets)

Output only the report. No preamble.

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. 9d ago First seen · 18 lines · 28 tokens per session scan A 3ea9d252d89a

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository Samuel0101010/wisp-orchestrator (4 stars, last pushed 5d ago), licensed Apache-2.0. It adds 28 tokens to every session and 165 once invoked, about $0.0001 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.

Related

Other skills, from other repositories

improve

Autonomous quality improvement loop. Scores a target against a rubric, selects the highest-leverage axis, attacks it, verifies, documents, and loops. No pre-planning between iterations — each loop re-scores from scratch.

SethGammon/Citadel · 48 tokens

evolve

Research-driven multi-cycle improvement director. Forms causal hypotheses about why scores are low, validates them with scout agents before attacking, dispatches axis-parallel fleet attacks, extracts transferable patterns, and runs indefinitely within a budget envelope. Accumulates a persistent belief model and…

SethGammon/Citadel · 60 tokens

research

Focused research investigations. Converts questions into structured findings with confidence levels and source citations. Single agent by default; with --parallel (or when the question decomposes into 3+ independent angles) it spawns scout agents whose findings are compressed into a unified brief. Does not make…

SethGammon/Citadel · 67 tokens

pr-watch

Local PR watcher. Monitors CI status, automatically fixes failing checks by reading failure logs and applying targeted fixes, then optionally merges when all checks pass. Local CLI analog to Claude Code's cloud auto-fix feature.

SethGammon/Citadel · 46 tokens

triage

GitHub issue and PR investigator. Pulls open issues/PRs, classifies them, searches the codebase for root cause or reviews contributed code, proposes fixes with file:line references, and optionally implements fixes. Use for investigating GitHub issues and reviewing PRs; do NOT use for general code review unrelated to…

SethGammon/Citadel · 71 tokens

watch

File sentinel that monitors the working directory for changes and marker comments, then auto-triggers appropriate skills. Poll-based via git diff against the last scan commit. Writes intake items for batch processing and routes marker actions through /do. Use for automatic reactions to file changes; do NOT use for…

SethGammon/Citadel · 70 tokens