smithery.ai

deepr-research

Use Deepr for bounded deep research, async cited reports, and consultation with persistent domain experts. Trigger when a user asks for current sourced analysis, a research cost preview, a domain expert or expert council, or inspection of durable beliefs, gaps, confidence, and provenance.

First seen Apr 5, 2026

Installation

$ npx skills add https://smithery.ai

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from smithery.ai · top by installs.

npx skills add https://smithery.ai

Browse all from smithery.ai

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code
More metadata
deepr-version
2.50.13
deepr-mcp-server
deepr

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 7,274 B
  • docs SUMMARY.md 607 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Deepr research

Use Deepr as a bounded research and persistent-expert service. Preserve citations, budget posture, capacity provenance, uncertainty, and dissent.

Release-safe operating contract

Treat these as works-now surfaces in the current release:

  • Write-free API research previews when the provider, model, tools, token

ceilings, and price are all known. Production paid dispatch remains blocked.

  • Explicit local Ollama or non-metered plan-quota expert workflows.
  • Read-only expert state, handoffs, loop status, memory cards, and derived

exports.

  • One-expert or multi-expert consultation through explicit local or eligible

plan synthesis. Metered council synthesis remains blocked even with approval and a positive budget.

Treat these as execution-blocked, even if a tool or flag remains visible:

  • deepragenticresearch and other autonomous multi-round metered work.
  • deepr_research paid execution and metered council synthesis.
  • deeprqueryexpert with backend="api" or agentic=true.
  • Automatic cross-provider metered fallback.
  • Metered batch, campaign, team, prepared, or continuation execution.
  • Hosted upload, file-search, or vector-store attachment to research.
  • Generic metered expert creation, learning, resume, refresh, gap fill,

reflection, portrait generation, or corpus calibration.

Do not retry a blocked surface with a larger budget or another provider. A capacity gate means the accounting contract is unavailable, not that the user asked a bad question.

Select capacity explicitly

  1. Prefer existing expert state when it already covers the question.
  2. Prefer backend="local" for a true $0 marginal-cost expert turn when an

admitted Ollama model is ready.

  1. Use backend="plan" only with an explicit non-metered plan id. Do not infer

that CLI presence proves free quota. A visible backend is not proof of executable plan capacity.

  1. Use the CLI's write-free API research preview to inspect a finite envelope.

No user budget or approval installs the missing provider account-control and credential-identity proof needed for production paid dispatch.

  1. Never silently fall through between capacity classes.

Preview one bounded research job

Use this sequence:

  1. State that the budget is a maximum, not a predicted final charge.
  2. Inspect the advertised tool schema; a visible metered tool is not executable

capacity. The CLI supports deepr research QUESTION --provider PROVIDER --model MODEL --preview without a paid request.

  1. Keep hosted files, paid tools, automatic fallback, and inference disabled.
  2. Report the estimated maximum and the dispatch block separately. A preview

produces no submitted job or completed research report.

  1. Existing accepted job state and completed reports remain inspectable through

deeprcheckstatus and deeprgetresult.

Do not invent fixed prices or promise a completion time. Model rates, tool charges, provider latency, and the hard request envelope determine the admission result. If the envelope exceeds the approved budget, stop and return the denial rather than weakening the ceiling.

Consult persistent experts

Start by calling deeprlistexperts and, when useful, deeprgetexpert_info. Then choose one of these no-metered paths:

deepr_query_expert(
  expert_name="Security Analyst",
  question="What evidence should guide this decision?",
  backend="local",
  agentic=false,
  budget=0
)
deepr_query_expert(
  expert_name="Security Analyst",
  question="What evidence should guide this decision?",
  backend="plan",
  plan="claude",
  agentic=false,
  budget=0
)

For several experts, prefer deeprconsultexperts with synthesisbackend="local" or synthesisbackend="plan". Keep the roster at 10 or fewer, preserve disagreements, and verify that capacity.livemeteredfallback is false.

An expert answer is a perspective over stored state, not ground truth. Surface confidence, contested beliefs, stale evidence, missing sources, and known gaps. Do not claim that a fresh research report was permanently absorbed unless a separate verified write workflow actually completed.

Handle local capacity defensively

For scheduled local maintenance, treat busy as a waiting outcome. Preserve the returned retry time and do not fall through to plan or API capacity. Expected retry guidance uses bounded 30-minute, 2-hour, then 6-hour cadence. Explicit unscheduled local work is an operator override; do not simulate that override on the user's behalf.

Present results

  • Lead with the answer.
  • Preserve every citation marker and source URL returned by Deepr.
  • Separate research-derived claims from your own inference.
  • Include provider/capacity, actual settled cost, and important limits.
  • Preserve council dissent instead of flattening it into false consensus.
  • Say when semantic quality is unreviewed. Structural eval success is not proof

that an answer is true or wise.

Tool guide

Tool Use
deeprtoolsearch Discover a current tool schema before calling it
deepr_status Inspect service readiness and spending posture
deepr_research Visible metered tool; production paid dispatch is blocked
deeprcheckstatus Inspect an accepted job
deeprgetresult Retrieve a completed cited report
deeprcanceljob Request cancellation and retain accounting state
deeprlistexperts List persistent experts
deeprgetexpert_info Inspect expert profile and gaps
deeprqueryexpert Run one local or plan read-only expert turn
deeprconsultexperts Produce a bounded one- or multi-expert consult artifact

Error handling

  • BUDGETEXCEEDED or BUDGETINSUFFICIENT: report the ceiling and capacity

block; a larger budget cannot enable quarantined production dispatch.

  • PROVIDERNOTCONFIGURED: identify the missing explicit capacity without

switching providers.

  • meteredexpertchataccountingunavailable or another capacity block: use

local/plan read-only consultation or stop.

  • Busy local capacity: report the durable wait and retry time.
  • Ambiguous provider failure: do not resubmit automatically. The reservation

may have been conservatively settled.

Read these only when needed:

  • [Research modes](references/research_modes.md) for the exact works-now and

gated research boundary.

  • [Expert system](references/expert_system.md) for read-only consultation and

verified update boundaries.

  • [Cost guidance](references/cost_guidance.md) for ceilings and ledger rules.
  • [MCP patterns](references/mcp_patterns.md) for discovery, resources, and

host-agent contracts.

  • [Troubleshooting](references/troubleshooting.md) for typed failure handling.
  • [Prompt patterns](references/prompt_patterns.md) for bounded research prompts.