dsh-auto-review
PerryLink/dsh-auto-review
Second-model auto-review on the approval answerer chain: a read-only reviewer subagent returns structured allow/deny verdicts with reasons, fail-closed by default.
Install
Add dsh-auto-review to DeepSeek Harness
via npm
Resolves a published tarball rather than cloning the repository, and installs without any extra setup. Swap `web` for your profile name if you run another one.
via GitHub · npm package
Installing from GitHub runs the project's build script, which pnpm blocks until you allowlist it — run the command once and pnpm prints the exact key to add under `allowBuilds` in ~/.dsh/profiles/web/pnpm-workspace.yaml.
What happened when we ran it
Installed cleanly when we ran it
Every command here is run in a throwaway container against a clean profile, and the result is whatever the harness recorded — not a guess from the source. Last run 6d ago.
Due diligence
Before you install dsh-auto-review
- Source of record: PerryLink/dsh-auto-review — present in the community registry that DSH's own plugin market installs from.
- Licensed under Apache-2.0.
- Detected: terminal surface, requires credentials. Read the source before granting these.
- A listing here is not a security review. Plugins run with your agent's permissions.
The AI take
What it is — DeepSeek Harness plugin providing second-model auto-review on the approval chain.
Who it is for — When you use an agent in DeepSeek Harness to handle sandbox boundary actions, needing structured allow/deny review results. If your workflow relies more on human approval rather than subagent decisions, you don't need to install this plugin.
Watch out — Sandbox test passed, successfully installed in new profile and registered by harness. Requires providing API key or token upon installation. Will execute shell commands.
The verdict — I would install it because it implements a fail-closed default policy that prevents unsafe actions from passing when review fails.
Generated by grok-4.6, and a starting point rather than a verdict. Where it says a plugin installs or does not, that is from a real run in a clean profile — everything else is read off the repository. Trust the source over this.
What dsh-auto-review does

dsh-auto-review is a DeepSeek Harness plugin that adds a second-model, read-only review step to approval requests before actions cross the sandbox boundary. DeepSeek Harness loads an approval/request answerer that claims requests covered by the ai policy and delegates other requests with next(), preserving the existing human approval chain. For an AI-reviewed request, a one-shot reviewer subagent reads the workspace with read, glob and grep, the streamed tool-call arguments with sensitive values redacted, the request reason and configured risk rules. It returns { decision, reason, riskLevel }; the reason is linked to the denied tool result by callId.
The default fallbackPolicy is rejected, so a reviewer crash, timeout or schema mismatch fails closed. autoReview/verdict and autoReview/rejection events provide a session audit trail, while /auto-review on, /auto-review off and /auto-review approve control session behaviour. Policies and limits are configured in cordis.yml, including toolsPolicy, riskRules, reviewerModel, reviewerTimeoutMs and reviewerTools.
dsh-auto-review suits workflows that need model-based evidence review without giving the reviewer write or terminal tools. It is the wrong choice when every request should remain a human decision, or when a second model and its credentials should not inspect workspace evidence. The listed risk surface includes a terminal surface and required credentials; the shipped policy reviews bash and write with AI, while other tools, including edit, remain on the human chain unless configured otherwise.
dsh-auto-review documentation
How dsh-auto-review behaves
DeepSeek Harness invokes the plugin on the approval/request answerer chain. The plugin recognises reviewer requests by identity and delegates them, while the reviewer child is bounded by maxDepth and its non-empty reviewerTools allow-list. Each decision follows approval/asked to autoReview/verdict or autoReview/rejection, then approval/decided. Audit events are log-only and marked ignorable: true. An optional invariant companion checks that rejection markers and events correspond.
A deny reason is injected into the calling model's denied tool result. Fallback and never decisions add [auto-review-fallback] and [auto-review-never] markers. The rejection circuit breaker acts after three consecutive denials, or six of the last ten verdicts, per turn.
Configuring dsh-auto-review
DeepSeek Harness reads these Schemastery fields from cordis.yml. An id-targeted override replaces the complete row, so required keys must be restated.
| Key | Default | Purpose |
|---|---|---|
enableByDefault |
true |
Initial session state; /auto-review on|off creates a durable override |
toolsPolicy.default |
human |
Policy for unlisted tools |
toolsPolicy.overrides |
{} |
Per-tool ai, human or never policy |
riskRules |
[] |
Regex rules for reason, toolName or arguments |
reviewerModel |
inherit | Reviewer model route |
reviewerTimeoutMs |
60000 |
Verdict deadline |
fallbackPolicy |
rejected |
Failure result: rejected, delegate or allow-once |
maxReviewsPerTurn |
10 |
AI-verdict budget |
maxFailuresPerTurn |
10 |
Reviewer-failure budget |
Other documented fields include reviewerProvider (fork), reviewerTools ([read, glob, grep]), reasonMaxChars (2000), reviewerGuidance, reviewerPolicyText and denyGuidance.
Commands and requirements
DeepSeek Harness provides /auto-review on, /auto-review off and /auto-review approve. The last is a one-shot override. The plugin targets DeepSeek Harness 0.1.1-rc.2, with peers >=0.1.0-rc.8 <0.2.0, and requires Node ^22.19.0 || >=24.0.0. It supports all platforms as a host answerer; the optional Web review panel uses the session-projection capability. The reviewer inherits the session agent's route unless reviewerModel is set.
Written from the project's own documentation and kept in sync with it. Where the two disagree, the source is authoritative — read the README on GitHub
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