deep-research

deep-research is a skill for Codex from OutlineDriven/outline-driven-development. It costs 34 tokens per session (1,723 once invoked), scanned A, original, Apache-2.0.

A sourced Markdown report created from thorough research on a chosen topic, with findings, recommendations, and risks.

In plain words
What is it for?
Use it for market, technical, product, academic, legal, financial, competitive, or other structured research.
Why use it?
It gathers evidence into one document so decisions do not rely on scattered or unsupported information.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents.

Good fit Use it for market, technical, product, academic, legal, financial, competitive, or other structured research.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/outlinedriven/outline-driven-development/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 OutlineDriven/outline-driven-development --skill deep-research
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/outline-driven-development

Made for: Codex.

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/outlinedriven/outline-driven-development/deep-research/github.svg)](https://agentmods.dev/skills/outlinedriven/outline-driven-development/deep-research)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/deep-research"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/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/outlinedriven/outline-driven-development/deep-research"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,723 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 pass 7 Sept 2026
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 $0.00034 $0.01723
Opus 5 $0.00017 $0.00861
Sonnet 5 $0.00007 $0.00345
Haiku 4.5 $0.00003 $0.00172

Measured 2d ago against content hash 783077d18be3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, 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 2d 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.

.devin/skills/deep-research/SKILL.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep research

Contract

Field Bound contract
Trigger User asks to research a topic and produce a thorough sourced report.
Authority Reversible local: writes only ./research/{type}-{topic}-{YYYY-MM-DD}.md (or the optional output-path override) and an optional PDF beside it; rollback is version control or undo. No remote mutation. Spawns 3-20 read-only sub-agents.
Side effect Writes ./research/{type}-{topic}-{YYYY-MM-DD}.md; optionally exports a PDF beside it. Sub-agents perform read-only web search and page fetch. Output path can be overridden with the optional output-path input.
Done A prose-first cited Markdown report exists at the output path, containing key findings, strategic recommendations, and risks/uncertainties, with every claim cited.

Inputs

  • Topic and research type, supplied by the user or inferred from the prompt. Research types: market, domain, technical, competitive, product, academic, person/org, financial, legal, trend, community. If none fit, infer a type and design a matching axis breakdown.
  • Specific questions or goals the research must answer (optional for well-scoped prompts; required for vague prompts).
  • Geographic, time, or segment constraints (optional).
  • Output path override (optional; default ./research/{type}-{topic}-{YYYY-MM-DD}.md).
  • PDF export request (optional).
  • Web access is required; if unavailable, halt.

Procedure

  1. Get today's date with date +%Y-%m-%d; use it for date-filtered searches and recency references throughout. Done when: today's date is obtained and used for date-filtered searches.
  2. Scope. If the prompt is specific and well-scoped (topic, type, and goals clear), infer the research type, state assumptions explicitly in the report header, and proceed. If vague or ambiguous, ask the user one question at a time with 2-4 options: what type, what specific questions or goals, and any geographic/time/segment constraints. Check whether a report on this topic already exists in the output directory; if found, ask whether to extend or start fresh. Set the output path to the supplied output-path override when one is given, otherwise to ./research/{type}-{topic}-{YYYY-MM-DD}.md (lowercase, hyphens). Write the report header now (topic, type, goals, date, assumptions, methodology note). Done when: the output path is set and the report header is written with topic, type, goals, date, assumptions, and methodology note.
  3. Core research: parallel fan-out. Spawn 3-20 sub-agents in a single message, one per research axis for the chosen type. Each sub-agent searches its axis on the web, fetches the sources it cites, writes findings as prose paragraphs with inline citations (not bullet lists), and returns URL, accessed date, and a confidence level per claim. Each sub-agent tags every source as Primary (official docs, filings, peer-reviewed), Established (major publications, analyst firms), or Low (blogs, forums, single opinions) and flags Low-tier sources prominently. Sub-agents do not wait for each other. Append each sub-agent's findings to the output file under the matching section heading immediately as it completes. Never batch. Done when: every core-research sub-agent's findings are appended to the output file immediately as completed.
  4. Competitive/landscape analysis: parallel fan-out. Spawn 3-5 sub-agents covering the landscape axes for the chosen type with the same citation discipline. Append results immediately. Done when: every landscape sub-agent's findings are appended immediately.
  5. Deep dive: parallel fan-out. Spawn sub-agents covering the deep-dive axes for the chosen type. Append results immediately. Done when: every deep-dive sub-agent's findings are appended immediately.
  6. Outline refinement (deep mode only, selected when the user says "thorough", "exhaustive", or "comprehensive"). After steps 3-5, review whether evidence warrants restructuring: did findings contradict the initial scope, did an important angle emerge, are any sections underpowered or overloaded. If yes, adapt the outline, run 2-3 targeted gap-fill searches time-boxed to 5 minutes, and record what changed in the methodology note. Skip in quick mode (narrow, time-sensitive: run steps 2 auto-scope, 3, 7) and standard mode (steps 2-5, 7; step 6 is deep-only). Done when: the outline is refined with gap-fill searches run and changes recorded, or the step is skipped per mode.
  7. Synthesis. Read the full output file and write the synthesis section: Key Findings (5 critical insights as prose paragraphs, each with a source reference), Strategic Recommendations (3-5 ranked by impact, each with rationale and evidence), Risks and Uncertainties (data gaps, low-confidence claims, unresolvable source conflicts, domain/market risks to monitor), and Next Steps (follow-up research, whether the initial request is fulfilled or needs another scope loop, decisions this research enables). Use extended reasoning here: reconciling conflicting multi-source data and ranking recommendations requires deep inference. Keep the fact/synthesis distinction throughout: "According to [Source], X" for sourced claims; "This suggests Y" for analysis. Done when: the synthesis section contains Key Findings, Strategic Recommendations, Risks and Uncertainties, and Next Steps with the fact/synthesis distinction maintained.
  8. Critique pass (deep mode only). Red-team the synthesis: what is missing, what could be wrong, what alternative explanations exist, what biases might be present. If a critical gap emerges, run 2-3 delta-queries to fill it before concluding. Done when: the synthesis is red-teamed with delta-queries run for critical gaps, or the step is skipped per mode.
  9. PDF export (optional, only if the user requests it). Check converter availability with which pandoc and which md-to-pdf. Try pandoc first (pandoc <output-path> -o <pdf-path>), then md-to-pdf (md-to-pdf <output-path>). If neither is available, tell the user to install pandoc or md-to-pdf. Done when: the PDF is exported next to the Markdown or the user is told which converter to install, or the step is skipped when no PDF was requested.

Read the full file on GitHub · 48 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 Changed · -18 tokens per session 783077d18be3
  2. 5d ago First seen · 48 lines · 52 tokens per session scan A de55b2d20373

Subscribe to this mod's changes

deep-research is a skill published in the GitHub repository OutlineDriven/outline-driven-development (52 stars, last pushed 3d ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,723 once invoked, about $0.0002 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 2026-09-03.

Related

Other skills, from other repositories

audit-project

Run an iterative multi-agent code audit until critical and high findings are resolved. Use when the user says "audit my code", "find all the bugs", "deep code audit", "iterative review", or "review until clean".

OutlineDriven/odin-claude-plugin · 50 tokens

duet

Use when the user invokes /duet, says "pair with me", or faces aesthetic, architectural, or irreversible decisions.

OutlineDriven/odin-claude-plugin · 28 tokens

goal-prompt-drafting

Use when asked to draft copy-ready /goal objectives for long-running agents; returns one normalized one-line objective with measurable end state, grounded proof, easy-out invariants, a stop clause, and a Missing list. Not for source or remote-system changes.

OutlineDriven/odin-claude-plugin · 57 tokens

handoff-prompt

Use when the user asks for a handoff, delegation, or clipboard-ready prompt for another agent: a standalone path-free prompt copied to the clipboard, confirmed by title. Not for session-snapshot briefs — use handoff; never remote, credential, publish, deploy, or irreversible.

OutlineDriven/odin-claude-plugin · 62 tokens

publish-branch

Use when asked to publish the checked-out branch: commit and push it on whatever branch it is, the default branch included. Not for creating branches, PRs, force pushes, or pushing any other branch; when the request excludes the default branch, use commit-push-current.

OutlineDriven/odin-claude-plugin · 60 tokens

snippet-image-rendering

Use when the user explicitly names snipgrapher and wants code rendered to a polished PNG, SVG, or WebP at an explicit local path. Probes the installed CLI for supported flags and writes only the named image file. Not for other renderers, publishing, or remote actions.

OutlineDriven/odin-claude-plugin · 64 tokens