Agent skill

run-deep-research

Quellcode ansehen: yigitkonur/skills-by-yigitkonur

#201Globales Ranking · von 201 SkillsMedium

Installation

npx skills add yigitkonur/skills-by-yigitkonur --skill run-deep-research

4

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EU-hosted inference API

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MiniMax

MiniMax M3

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GLM 5.3 Flash

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MoonshotAI

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DeepSeek

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Run Deep Research

This skill orchestrates a multi-file evidence corpus on disk, never a single chat reply.
Per-entity evidence packs, cross-axis comparison rollups, source ledgers, optional
profile pages, and a master summary — all written into a navigable folder tree the
user can read, edit, link from, and re-enter later. The filesystem is the deliverable.

The orchestrator operates as the system architect, delegator, gatekeeper, and synthesizer.
The orchestrator does not search the web personally; instead, it decomposes the research
domain, structures the folder tree, dispatches focused research to parallel background
subagents in orchestrated waves
, gates and audits between waves, and personally synthesizes
the final decision artifacts. Every research subagent inherits the run-research discipline
(3-tool research surface, ## Not found harvesting, verified verbatim quotation citations,
and multi-round scope refinement).

The filesystem is the context channel between waves. Subagents do not see each other's
in-flight context; they read only the specific files named in their brief and write only to
their assigned directory.

When to use this skill

Trigger on any of these phrasings:

  • "research / compare / evaluate 5+ tools / vendors / projects / frameworks"
  • "market analysis of [category] / competitive landscape / category map / competitor research"
  • "build a research corpus / evidence pack / decision corpus on [category]"
  • "deep research on [SaaS / OSS / dev-infra / data-API / regulated category]" with per-vendor pages
  • "give me pricing + capability + integration + security + audience matrices across [vendors]"
  • "navigable folder of product pages, comparison rollups, source ledgers, and profile pages"
  • "every numeric / versioned / priced claim must cite a verbatim source quote"
  • "the deliverable is a folder tree the team can navigate", not a chat reply
  • "audit / shortlist [population]" against a fixed axis catalog (cost, performance, fit, risk, longevity)
  • The user names 5+ vendors / projects upfront and asks for a structured side-by-side comparison

Do NOT use when:

Situation Use instead
One technical question, single answer run-research
1-4 entities, one polished single-page summary, no folder structure run-research
Finding or shortlisting GitHub repos as the deliverable run-github-scout
Codebase analysis, code review, or implementation work not this skill
Polished single deliverable (HTML battlecard, slide deck) downstream skills polish

The fence: run-research answers one question and returns one synthesis;
this skill answers N questions across N entities and returns a multi-file
corpus
. If the deliverable is a folder, you are in this skill. If it's a chat
reply or a single Markdown file, you are in run-research.

Intake — always ask first (AskUserQuestion)

Before any decomposition, template authoring, or subagent dispatch, run one batched
AskUserQuestion call
to lock the run's shape. This is mandatory — never start a
heavy pass on assumptions. Batch the discrete decisions into a single call so the user
answers once; make the recommended default the first option of each:

  1. Scale — standard (10-40 entities, ~150-500 files) · compact (5-10 entities, ~80-200 files) · deep (40-100 entities) · tiered (100+ entities).
  2. Framing — industry / vendor category (market analysis, pricing, profile pages) · domain-agnostic corpus (OSS projects, papers, architectures).
  3. Scope & Discovery — discover entities vs use user's named list; confirm <topic-slug>/ output folder and whether profile pages are wanted.
  4. Concurrency — standard (6-8 parallel subagents per wave) · conservative (3-4 subagents) · high throughput (10-15 subagents).

Capture the decider and use case from the conversation (or free-text notes) —
these anchor _meta/01-charter.md; without them "good" and "bad" are undefined.
If AskUserQuestion is unavailable (non-interactive run), fall back to the stated
defaults and record the assumption in the charter. Full question wording, option sets,
recommended defaults, and the headless fallback: references/intake.md.

The Universal Subagent Architecture

The research executes across a modular, 2-level multi-agent hierarchy:

                      ┌────────────────────────────────────────┐
                      │              ORCHESTRATOR              │
                      │  (Intake, Architecture, Gates, Master) │
                      └───────────────────┬────────────────────┘

                  ┌───────────────────────┼───────────────────────┐
                  ▼                       ▼                       ▼
       ┌─────────────────────┐ ┌─────────────────────┐ ┌─────────────────────┐
       │   WAVE 1 SUBAGENTS  │ │   WAVE 2 SUBAGENTS  │ │   WAVE 3 SUBAGENTS  │
       │ Discovery & Axes    │ │ Per-Entity Packs    │ │ Cross-Axis Rollups  │
       │ (run-research web)  │ │ (run-research web)  │ │ (local-only corpus) │
       └─────────────────────┘ └─────────────────────┘ └─────────────────────┘
  • Orchestrator: Owns chartering, maximalist template authoring, file budget, wave dispatch, between-wave evaluation gating, and master summary synthesis.
  • Research Subagents (Waves 1, 2, 4-promoted): Autonomous background workers executing the run-research web discipline (plan-research → parallel web-searchextract-evidence with verbatim quotes and locator matching).
  • Synthesis Subagents (Wave 3, Wave 4 profiles): Local-only workers synthesizing comparative matrices, trade-offs, and rankings directly from existing corpus files without web searching.
  • Filesystem Blackboard: Read scopes and write scopes are strictly disjoint. Subagents interact exclusively through committed files on disk.

Phase & Wave Model

Eight structured phases, each protected by an artifact gate:

Phase Goal Artifact gate
0 — Charter Apply intake answers; clarify decider, use case, scale, framing, concurrency _meta/01-charter.md scope statement + scale + framing + decider profile
Wave 1 — Discovery & Scope Parallel dispatch of 2 subagents: 1A discovers/tiers entities; 1B derives axis catalog & native primitives. _meta/02-entities.md (or discovered-entities.md) + _meta/03-axes.md + practitioner channel list
2 — Template Authoring Orchestrator personally writes maximalist product & per-axis comparison templates. Target ~30+ vertical-specific sections. _meta/04-product-template.md + _meta/05-axis-templates.md (or _meta/_PRODUCT_TEMPLATE.md + per-criterion templates)
3 — Corpus Architecture Design tree shape, calculate file budgets, enforce MAX-N ceilings. Scaffold folders via scripts/init-corpus.sh. _meta/06-file-budget.md + pre-created folder skeleton
Wave 2 — Per-Entity Packs Fill <entity-slug>/ for every core entity (parallel, ≤8 per sub-wave). Disjoint write scopes. Each covers all charter axes. Populated <entity-slug>/ packs; every section covered with evidence or specific "insufficient evidence" gap note
Wave 3 — Cross-Axis Synthesis Compare entities along each axis. LOCAL-ONLY (no web tools). Each subagent owns one cross folder. Populated _cross/<axis-slug>/ or _cross-<scope>/ with rankings + matrix + decision-flippers
Wave 4 (Optional) — Profiles / Deepening Standalone <entity-slug>.md decision pages at corpus root (LOCAL-ONLY) OR research packs for promoted entities. Profile pages OR new entity packs
7 — Verification & Master Summary Orchestrator personally reads every file, resolves contradictions, writes master summary, and executes quality audit. _meta/00-master-summary.md + passing 6-dimension evaluation audit

Output Architecture Contract

Domain-agnostic framing tree:

<corpus-root>/
├── README.md                                       (entry point)
├── _meta/                                           (MAX 8 files)
│   ├── 00-master-summary.md                        (Phase 7)
│   ├── 01-charter.md                               (Phase 0; Wave 1 resolves)
│   ├── 02-entities.md                              (Wave 1A output)
│   ├── 03-axes.md                                  (Wave 1B output)
│   ├── 04-product-template.md                      (Phase 2)
│   ├── 05-axis-templates.md                        (Phase 2)
│   ├── 06-file-budget.md                           (Phase 3)
│   └── 07-dispatch-log.md                           (running log)
├── <entity-slug>/                                   (one per core entity; MAX 15 files)
│   ├── 00-overview.md
│   ├── 01-<axis-1>.md ... 0N-<axis-N>.md
│   └── 09-sources.md
├── <entity-slug>.md                                 (optional profile page at root)
└── _cross/
    └── <axis-slug>/                                (MAX 12 files)
        ├── 00-overall-comparison.md
        └── 01-<scenario>.md ...

Industry framing tree:

<topic-slug>/
├── README.md
├── _meta/
│   ├── research-plan.md
│   ├── _PRODUCT_TEMPLATE.md                        (Phase 2 maximalist template)
│   ├── _COMPARISON_TEMPLATE_<criterion>.md         (Phase 2 per-criterion)
│   ├── methodology-and-source-policy.md
│   ├── discovered-entities.md
│   └── file-budget.md
├── _cross-<scope>/
│   ├── 00-overview/
│   ├── <criterion-a>/
│   ├── <criterion-b>/
│   └── 09-sources/
├── <entity-slug>/
│   ├── 00-overview/
│   ├── <vertical-context-1>/
│   ├── <vertical-context-2>/
│   └── 09-sources/
└── <entity-slug>.md                                 (profile page; Phase 6/Wave 4)

Folder and file naming rules, MAX-N ceilings, and numbered-prefix schemes: references/filesystem.md.
Category taxonomy archetypes: references/industry/category-taxonomies.md.

How to Evaluate a Deep-Dive Corpus

Every deep research deliverable must pass the 6-Dimension Evaluation Audit before completion:

  1. Structural & Budget Integrity:
    • Strictly adhere to MAX-N caps (≤15 files/entity, ≤12 files/cross, ≤8 files/meta).
    • Zero temporary files, empty stubs, or placeholder strings (TODO, TBD, fill later).
    • All internal relative markdown links resolve correctly.
  2. Template Coverage & Gap Specificity (The 100% Rule):
    • Every core entity folder must address 100% of the axes locked in _meta/03-axes.md.
    • An axis must have either substantive evidence OR a concrete "insufficient evidence" entry explaining what was searched, which primary sources were checked, why data is unavailable, and what resolution is required.
  3. Evidentiary Rigor & Verbatim Quotations:
    • Every numeric, performance, pricing, and version claim MUST cite a verbatim quotation with source URL and scrape date.
    • Search snippet citations are strictly forbidden — only fetched and verified page text counts.
    • Separate objective verified facts from vendor marketing claims and community sentiment.
  4. Community & Practitioner Attribution:
    • Sentiment (Reddit, HN, forums) must never be summarized as vague "consensus".
    • Every community claim must cite author handle, date, score/upvotes, and post link.
  5. Cross-Axis Comparative Synthesis:
    • Matrix cells in _cross/ must be fully populated (no empty cells; use explicit [No public data] markers).
    • Rankings must be conditional (e.g., "Vendor A for high-throughput, Vendor B for strict HIPAA compliance"), naming operational variables rather than flat assertions.
    • Disagreements between sources must be explicitly surfaced and analyzed.
  6. Decider Actionability & Fresh-Context Legibility:
    • The master summary (_meta/00-master-summary.md) must be self-contained and immediately actionable for a decider with zero prior context.
    • Must contain all 7 required sections: Document index, Critical findings, Cross-domain insights, Action items, Coverage scope, Open gaps, Recommendation.

Full evaluation rubric and automated audit commands: references/evaluation.md and references/verification.md.

Hard Rules (Load-Bearing)

  1. Run the intake AskUserQuestion batch before any wave. Scale, framing, and scope are locked at intake and recorded in the charter.
  2. The orchestrator does not search the web. Web search is delegated to research subagents using the run-research discipline.
  3. The orchestrator does not delegate final synthesis. The orchestrator personally reads every entity pack and cross file before writing the master summary.
  4. Templates first, files second. Phase 2 (template authoring) MUST complete before any entity pack or cross file is written.
  5. Maximalist templates, not generic skeletons. Target ~30+ vertical-specific sections.
  6. MAX 8 subagents per wave (domain-agnostic) / MAX 20 per wave (industry). Split larger batches into sequential sub-waves.
  7. Disjoint write scopes. Each subagent owns exactly one folder. No two subagents write to the same path.
  8. Every research brief embeds run-research. Subagent briefs must include the run-research methodology block.
  9. Every numeric / versioned / priced claim cites a verbatim quote. Snippet citations are forbidden.
  10. No placeholder or stub files. Missing evidence becomes a specific data-gap paragraph inside an existing file, never an empty stub file.
  11. Two-level orchestration only. Subagents do not spawn subagents.
  12. No single-report output. This skill produces a multi-file navigable corpus. For a single report, use run-research.

Self-Correction Triggers

  • Dispatching any wave before intake is answered → STOP. Run intake first; lock scale, framing, decider profile.
  • Skipping Phase 2 templates and dispatching Wave 2 → STOP. Templates establish the comparability contract.
  • Writing a thin or generic template (≤15 sections) → STOP. Re-author maximalist template (~30+ sections) per references/industry/template-authoring.md.
  • Letting a subagent silently omit a template section → STOP. Every section requires evidence or a specific data-gap entry.
  • Summarizing Reddit as "consensus" without attribution → STOP. Require username, date, score, quote, and permalink.
  • Searching the web yourself as orchestrator → STOP. Dispatch a research subagent.
  • Delegating master summary synthesis → STOP. Read all packs and cross folders personally.
  • Skipping the verification and evaluation gate → STOP. Execute the audit checks in references/evaluation.md and references/verification.md.

Reference Routing

Load only the reference whose phase is active:

Reference Read when
references/intake.md Before Phase 0 — mandatory AskUserQuestion batch: scale, framing, scope, concurrency
references/thinking.md Phase 0 — 7-question decomposition protocol, entities vs axes vs primitives
references/templates.md Phase 0, 2, 3 — formats for charter, product templates, axis templates, file budgets
references/orchestration.md Waves 1-4 — subagent wave choreography, parallel dispatch rules, between-wave gating
references/filesystem.md Phase 3 — directory contract, MAX-N ceilings, file naming schemes
references/subagent-briefs.md Waves 1-4 — copy-paste-ready subagent briefs with the run-research integration block
references/synthesis.md Phase 7 — claims ledger discipline, 10-section profile pages, 7-section master summary
references/evaluation.md Phase 7 & Between-Wave Gates — deep-dive evaluation rubric, 6-step audit workflow, triage protocols
references/verification.md Phase 7 — concrete bash/ruby verification commands and automated integrity checks
references/failure-modes.md Any wave — recovery protocols for timeouts, shallow outputs, contradictions, cap overflow
references/industry/template-authoring.md Keystone reference (industry framing) — writing maximalist _PRODUCT_TEMPLATE.md and per-criterion comparison templates
references/industry/industry-architecture.md Phase 3 (industry framing) — 4-layer industry tree, entity tiering, file budget derivation
references/industry/category-taxonomies.md Phase 2 (industry framing) — archetype taxonomies (SaaS, OSS, dev-infra, data/API, regulated, consumer)
references/industry/discovery.md Wave 1 (industry framing) — entity discovery sub-questions, tiering, deep category pre-pass
references/industry/evidence-and-synthesis.md Waves 2-3 (industry framing) — source hierarchy, claims ledger schemas, Reddit rules, unit economics
references/industry/profile-pages.md Wave 4 / Phase 6 (industry framing) — writing standalone <entity-slug>.md decision profiles
references/industry/mission-briefs.md Waves 1-4 (industry framing) — industry-specific mission prompts for subagents
references/industry/research-powerpack-and-explore.md Waves 1-3 (industry framing) — Research Power Pack API shapes (plan-research, web-search, extract-evidence)
references/industry/worked-example-cloud-browsers.md Any phase (industry framing) — complete annotated walkthrough of a reference research corpus
scripts/init-corpus.sh + scripts/init-corpus.md Phase 0 or 3 — deterministic corpus directory scaffolding

Quick Start (First 5 Minutes)

  1. Intake — run the batched AskUserQuestion call (scale / framing / scope / concurrency). See references/intake.md.
  2. Phase 0 — write _meta/01-charter.md from intake answers + decider/use-case. See references/thinking.md and references/templates.md.
  3. Wave 1 — dispatch parallel discovery (1A) and scope-mapping (1B) subagents. Both invoke run-research. Read outputs personally upon return.
  4. Phase 2 & 3 — write maximalist templates (references/templates.md or references/industry/template-authoring.md); plan file budget (references/filesystem.md); optionally run scripts/init-corpus.sh <topic-slug>.
  5. Wave 2 — dispatch parallel per-entity subagents (≤8 per sub-wave) to fill <entity-slug>/ packs.
  6. Wave 3 — dispatch parallel local-only subagents to build cross-axis comparisons in _cross/.
  7. Phase 7 — personally read all packs and cross files; write _meta/00-master-summary.md; run the 6-dimension evaluation audit in references/evaluation.md and references/verification.md.

So verwenden Sie diesen Skill

1

Install run-deep-research by running npx skills add yigitkonur/skills-by-yigitkonur --skill run-deep-research in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.

2

Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.

3

Der Skill verbessert das Verständnis Ihres Agenten für run-deep-research, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.

Was Sie erhalten

Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.

Kompatibilität

Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.