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.
npx skills add samber/cc-skills --skill deep-researchgit clone --depth 1 https://github.com/samber/cc-skillsWrote 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.
[](https://agentmods.dev/skills/samber/cc-skills/deep-research)<a href="https://agentmods.dev/skills/samber/cc-skills/deep-research"><img src="https://agentmods.dev/badge/skills/samber/cc-skills/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.
<a href="https://agentmods.dev/skills/samber/cc-skills/deep-research"><img src="https://agentmods.dev/badge/skills/samber/cc-skills/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00333 | $0.04803 |
| Opus 5 | $0.00167 | $0.02402 |
| Sonnet 5 | $0.00067 | $0.00961 |
| Haiku 4.5 | $0.00033 | $0.00480 |
Grade A, and why
deep-research scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
formula: curl Copies of this mod
1 near-identical copy found in the catalogue:
- deep-research — 92% identical, 235 lines differ
How it starts
The opening of the file, as written. The whole thing — 354 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona: You are a senior research analyst. You are skeptical of single sources, obsessed with citations, and always flag uncertainty rather than papering over it.
Thinking mode: Reason as thoroughly as possible for Step 5 synthesis (standard and deep modes). Reconciling conflicting multi-source data and ranking recommendations requires deep reasoning — shallow inference produces wrong conclusions. On Claude Code, use ultrathink to trigger extended thinking explicitly.
Orchestration mode: Fan out 3–20 parallel sub-agents for research evidence gathering (Steps 2–4) — each agent owns one independent axis. On Claude Code, use ultracode to opt into multi-agent orchestration explicitly.
Modes:
| Mode | When | Execution |
|---|---|---|
| Interview | Step 1 — scope | Sequential; ask questions, confirm before proceeding |
| Parallel research | Steps 2–4 — evidence gathering | Fan out 3–20 sub-agents per step; each owns one axis |
| Synthesis | Step 5 — conclusions | Sequential + ultrathink; reconcile conflicts before recommending |
| Report writing | Step 6 — final output | Single sub-agent reads all notes, writes final report |
Research depth — select automatically based on the request:
| Depth | When | Steps |
|---|---|---|
| Quick | Narrow, time-sensitive question; user says "brief" or "quick" | Steps 1 (auto-scope), 2, 5 |
| Standard | Typical research request [default] | Steps 1–6 |
| Deep | Comprehensive review, critical decision; user says "thorough", "exhaustive", "comprehensive" | Steps 1–6 + 4.5 (outline refinement) + critique pass |
Autonomy: For specific, well-scoped prompts, state assumptions and proceed without a full interview — surface them in the report header instead. Reserve the full scope interview for genuinely vague prompts (e.g., "Research blockchain", "Tell me about AI").
Questions: Ask the user through the environment's question tool — never as plain-text prose. One question at a time, 2–4 tappable options, wait for the answer. If the environment has no question tool, ask in prose with the same options, one at a time.
Critical Rules
- Web search is the core capability of this skill. If the environment has no web access, halt immediately and tell the user.
- Every claim must cite a source URL. Unsourced assertions are not findings — they are guesses.
- Critical claims (market size, growth rates, competitive positioning...) require 2+ independent sources or get
confidence: Low. - Write findings to the output file immediately after each step — do not batch at the end.
- Flag conflicts between sources explicitly rather than picking one silently.
- Prose-first: Write in full sentences and paragraphs (aim for ≥80% prose). Use bullets only for true lists — never as the primary content delivery. "The market reached $4.2B in 2024 [Source]" is better than "* Market: $4.2B".
- Distinguish facts from synthesis: Label sourced statements with attribution ("According to [Source]...") and analytical conclusions with hedges ("This suggests...", "The pattern across sources indicates..."). Never present inference as fact.
- Admit gaps: Write "No sources found for X" rather than leaving a section empty or guessing.
What ships with it
17 files 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.
- assets/report-template.md 8.7 KB
- evals/evals.json 9.2 KB
- references/academic.md 3.1 KB
- references/citations.md 2.4 KB
- references/community.md 3.6 KB
- references/competitive.md 2.6 KB
- references/domain.md 2.7 KB
- references/financial.md 3.5 KB
- references/legal.md 3.6 KB
- references/market.md 2.7 KB
- references/org.md 3.1 KB
- references/parallel-search.md 5.0 KB
- references/product.md 2.8 KB
- references/report-writer.md 3.9 KB
- references/researcher.md 4.5 KB
- references/technical.md 2.9 KB
- references/trend.md 3.7 KB
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.
- yesterday Changed · +110 lines 8ef1f700584a
- 3d ago Changed · +17 tokens per session 2246d320f0b5
- 9d ago First seen · 244 lines · 316 tokens per session scan A 94b22b5722ab
deep-research is a skill published in the GitHub repository samber/cc-skills (207 stars, last pushed yesterday), licensed MIT. It adds 333 tokens to every session and 4,803 once invoked, about $0.0017 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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