dsh-consult

dsh-consult

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Bring a second opinion to every decision that matters.

dsh-consult gives DeepSeek Harness an explicit, evidence-first review checkpoint. One agent does the work. When a decision deserves more scrutiny, 2–5 independently configured models receive the same brief and answer the same question. The main agent compares their anonymous opinions and remains accountable for the call.

/consult Finish the implementation and tests, then ask the panel whether this is ready to ship.

No background committee. No automatic model spend. No second team competing to edit the workspace.

Agent teams scale labor. dsh-consult diversifies judgment.

An agent team is useful when a task benefits from more hands: split the work, assign different roles, explore several areas, and combine the deliverables. As a mental model, it is one capable operator wearing several hats.

Consultation addresses a different problem. It is closer to inviting different reviewers into the same room, handing each of them the same evidence, and asking one carefully framed question. They do not divide the task or converge through discussion. The value comes from seeing where independent models agree, where they disagree, and what one model noticed that another did not.

	Agent team / subagents	dsh-consult
Optimizes for	Execution capacity	Decision quality
Work allocation	Different roles or subtasks	The same question for every model
Context	Gathered per assignment	One shared, selected evidence packet
Tools	Usually available	No tools, history, or workspace access
Output	Work products to merge	Independent opinions to assess
Spend	Grows throughout execution	Occurs only at an explicit checkpoint

This distinction matters because execution is often the predictable part once a direction is chosen. A strong main agent can implement, test, and verify a settled plan end to end. Keeping a committee of tool-using agents active throughout that process adds coordination, context, and tool-call cost even when there is little useful disagreement left. dsh-consult reserves model diversity for the moment when diversity is valuable, then hands ownership back to one agent.

Good moments for a second opinion

Use consultation for decisions with leverage or uncertainty:

• choosing between plausible architectures;
• reviewing a security, privacy, or data-retention boundary;
• challenging a migration or rollback plan;
• checking release readiness after the implementation is complete;
• examining subtle failure modes and recovery behavior;
• balancing performance, maintainability, compatibility, and user experience;
• testing whether a conclusion is robust or merely one model's preference.

Routine edits, obvious fixes, and already-settled execution usually do not need a panel. Consultation works best as a deliberate, high-value checkpoint—not a tax on every turn.

A controlled review loop

flowchart LR
    U["User requests /consult"] --> A[Main agent investigates and verifies]
    A --> P[One question + selected evidence]
    P --> C1[Model A reviews]
    P --> C2[Model B reviews]
    P --> CN[Models C–E review]
    C1 --> S[Main agent compares and synthesizes]
    C2 --> S
    CN --> S
    S --> R[Final recommendation]

The loop is intentionally opinionated:

• Opt-in only. External consultants are never called without /consult <task>.
• Work before review. The main agent investigates, implements, and validates before preparing the panel brief.
• A level playing field. Every consultant receives the same system prompt, question, constraints, and evidence.
• Independent answers. Calls run in parallel; consultants cannot debate, vote, or see one another.
• Anonymous synthesis. The main model sees stable labels such as Consultant A, not provider or model brands.
• One accountable owner. Advice informs the decision; it never replaces the main agent's judgment.
• Bounded cost. The operator controls panel size, routes, timeouts, generation limits, and accepted opinion size.

Quick start

You need Node.js >=22.19.0, a compatible DeepSeek Harness release, and at least two DSH model configurations, each identified by a provider and model.

1. Install the bundle

dsh plugin --profile web add dsh-consult

If you run DSH through a package runner:

pnpm dlx @deepseek-ai/dsh plugin --profile web add dsh-consult

2. Choose the panel

The bundle starts dormant and makes no model calls. Add this minimal override to ~/.dsh/profiles/web/cordis.patch.yml, or the equivalent profile under DSH_HOME:

- id: consult
  config:
    consultants:
      - provider: "<provider-id-a>"
        model: "<model-id-a>"
      - provider: "<provider-id-b>"
        model: "<model-id-b>"

Replace each value in angle brackets with its DSH identifier: provider names the model service and model names a model available through that service. Credentials stay in DSH settings and credential stores; dsh-consult neither reads nor saves API keys. The two provider IDs may be the same—for example, you can select two different models from one service. Only the complete provider + model pair must be unique. The example is the smallest valid panel; add more entries in the same form for a total of up to five consultants. Everything else is optional and falls back to a documented default; add those settings only when you want to tune them. See Configuration for the complete reference.

Verify the composed profile and start DSH:

dsh --profile web --dump-config
dsh web

3. Ask at the decision boundary

/consult Review the cache invalidation redesign. Inspect the implementation and tests first, then decide whether it is ready to ship.

The main agent continues normal workspace work and calls consult once the evidence is ready. A pending request can be cancelled with /consult off.

What remains under your control

• You select 2–5 model configurations and may tune reasoning effort for each one.
• Consultants run concurrently, so latency is normally set by the slowest route rather than the sum.
• A fully successful panel returns complete; one or more valid opinions return partial.
• Route identity, raw provider failures, usage, and timing remain in model-hidden diagnostic events.
• Durable intent and delivery state prevent recovery from silently repeating an external call that already started.
• Native Tool, PTC Mode, and ctx.consult.run(...) all require the same user-created intent.

Data leaves the workspace

The complete evidence packet is sent to every configured consultant and persisted in the DSH session event log. Version 0.2 does not discover or redact secrets. Before requesting a consultation, make two separate decisions:

• Is this material suitable for every external provider in the panel?
• Is it suitable for local session persistence, export, and backup?

Consultants cannot fetch more files or call tools, and evidence is framed as untrusted data. Those controls limit authority; they do not make sensitive material safe to disclose. Read Security and data flow before production use.

Tested compatibility

dsh-consult 0.2.0 supports only DeepSeek Harness 0.1.5-rc.2. Earlier and later DSH versions are unverified and are not guaranteed to work. Each plugin release supports one exact tested DSH version; “latest” is not a floating compatibility promise.

CI verifies this version on Node 22.19.0 and Node 24. The non-blocking DSH next monitor provides advance warning and never expands the support claim.

dsh-consult	Supported DSH
0.2.0	0.1.5-rc.2 only
0.1.0 (historical)	0.1.0-rc.7, 0.1.0-rc.8, 0.1.1-rc.1, 0.1.1-rc.2

Users of those older DSH versions can install dsh-consult@0.1.0 and consult its release documentation. See Compatibility for verification and release policy.

Documentation

Guide	Start here when you need to...
Configuration	Choose routes, reasoning effort, timeouts, and size limits
Usage	Understand intents, results, PTC Mode, and the service API
Security	Review external transmission, persistence, and deployment controls
Architecture	Follow fan-out, event settlement, durable delivery, and recovery
Compatibility	Verify a Node/DSH combination or add a new supported release
Releasing	Publish through npm and GitHub's release workflow

Development

pnpm install
pnpm check

The test suite composes real Cordis services with fake LLM adapters and a fake Code Runtime bridge; no model credentials are needed. pnpm verify:compat builds isolated temporary projects and leaves the current checkout untouched.

Contributions are welcome—start with CONTRIBUTING.md. Report security issues privately as described in SECURITY.md.

dsh-consult is an early public release for an evolving DSH developer preview. Pin a tested DSH version in production and read CHANGELOG.md before upgrading.

License

MIT