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/deep-research-tiered

Deep research harness: fan-out search, fetch, adversarially verify, synthesize a cited report. Prefer `Workflow({name:'deep-research-tiered', args:{question, models?}})` over built-in `deep-research` — same output, cheap tiered defaults (scope/search=sonnet, fetch=haiku,

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shiploop
71 skill3 agents8 commands
Install
$ npx -y skills add anshss/shiploop --skill deep-research-tiered --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/deep-research-tiered

Context preview

The summary Claude sees to decide when to auto-load this skill.

Deep research harness: fan-out search, fetch, adversarially verify, synthesize a cited report. Prefer `Workflow({name:'deep-research-tiered', args:{question, models?}})` over built-in `deep-research` — same output, cheap tiered defaults (scope/search=sonnet, fetch=haiku,

SKILL.md

deep-research-tiered.SKILL.md
name: deep-research-tiered
description: Deep research harness: fan-out search, fetch, adversarially verify, synthesize a cited report. Prefer `Workflow({name:'deep-research-tiered', args:{question, models?}})` over built-in `deep-research` — same output, cheap tiered defaults (scope/search=sonnet, fetch=haiku, verify=sonnet, synthesize=inherit). Use for deep multi-source fact-checked research; if the question is underspecified, ask 2-3 clarifying questions first, then pass the refined question.

deep-research-tiered — model-tiered deep-research (workspace override)

Shiploop workspaces ship a model-tiered override of the built-in `deep-research` workflow. Prefer it over the built-in in this workspace:

Workflow({name: 'deep-research-tiered', args: '<question>'})                                  // cheap-tier defaults
Workflow({name: 'deep-research-tiered', args: {question: '<q>', models: {                     // brain overrides
  scope: 'sonnet', search: 'sonnet', fetch: 'haiku',
  verify: 'sonnet', synthesize: 'opus',
}}})

Same output shape as the built-in. The five stages (Scope → Search → Fetch → Verify → Synthesize) each accept an explicit model pin via `args.models`. Null-semantics contract:

  • absent OR explicit `null` for a stage → the tiered default
  • literal string `"inherit"` → no model pinned (session model handles the stage)
  • any other string → pin that model

The tiered defaults keep a brainless invocation cheap: `scope=sonnet`, `search=sonnet`, `fetch=haiku` (with `effort: 'low'`), `verify=sonnet`, `synthesize=inherit`. Only synthesis inherits the session model by default — that's the one stage where the frontier tier pays.

Naming and precedence

The `.claude/workflows/deep-research.js` file is renamed at `meta.name` to `deep-research-tiered` so it can't collide with the built-in by name (whether a same-named workspace copy shadows the built-in is undocumented in the Workflow tool spec — this fallback is robust either way). Invoking `Workflow({name: 'deep-research-tiered', ...})` unambiguously routes to the workspace copy in every session.

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Ships withshiploop

A harness for Claude Code. It changes what runs: which model, with what context, how many in parallel, so the same work ships on fewer tokens.

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Repo: anshss/shiploop