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Benchmark — DSH Plugin for DeepSeek Harness
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dsh-benchmark

Benchmark

Reproducible deterministic benchmark evidence for DSH tools and plugins

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add github:dongsheng123132/dsh-benchmark#3f48afaa5ad7bd4b1214e048bf1eae18f98b0cf0
READMECompatibilityVersions

Compatibility and provenance

Benchmark is published as dsh-benchmark and currently resolves to version 0.2.1. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
any
Release source
github
Registry updated
9/7/2026

Versions

0.2.1stable
9/7/2026

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0.2.1
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License
MIT
Source
github
GitHub
★ 3
Weekly downloads
0
Last push
9/7/2026
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README

dsh-benchmark

Reproducible, deterministic benchmark evidence for DeepSeek Harness tools and plugins.

This project deliberately does not duplicate dsh-batch-regression, which runs one shell command repeatedly for median/distribution statistics. dsh-benchmark defines an evidence protocol around fixed cases: explicit target and suite revisions, file-derived target fingerprints, bounded argv-only subprocesses, raw measurements, versioned deterministic scoring, content-addressed reports, and baseline regression comparison.

The first release evaluates commands and JSONL runners, not subjective LLM quality.

Version 0.2.0 is a formal Codex plugin and standalone proof-only MCP server, and uses the namespace export shape required by the stock DSH Web Loader. A real Cordis boot regression test guards that loader contract.

Adjacent benchmark skills often grade Skill or LLM quality. This project stays at the deterministic execution-evidence layer: fixed target revisions and cases, raw bounded measurements without raw business output, versioned scoring, content-addressed reports, and baseline regression decisions.

Evidence model

An explicit manifest freezes:

  • suite name and case revision;
  • target name, claimed revision, and files used to recompute its fingerprint;
  • executable, constrained working directory, warmup/repeat counts, timeout, output cap, and concurrency cap;
  • fixed argv and optional JSONL stdin for every case;
  • expected exit code, stdout/stderr SHA-256, and optional JSONL line count;
  • scorer version, minimum pass rate, output-stability rule, and maximum median-latency regression.

Each run records warmup and measured observations separately: duration in nanoseconds, exit code, signal, timeout/output-limit state, output byte counts and hashes, JSONL validity, and every expectation check. Raw argv, stdin, stdout, stderr, inherited environment, timestamps, and hostnames are excluded from reports.

Safety model

  • shell: false; no command strings or shell interpolation.
  • node maps to the current absolute process.execPath. Other executables must be explicit workspace-relative regular files; PATH lookup is not used.
  • cwd, target files, manifests, reports, and artifact directories cannot escape workspaceRoot through traversal or symlinks.
  • Child processes receive a minimal deterministic environment instead of inherited secrets.
  • Timeout, captured-output bytes, and concurrency are mandatory bounded manifest values.
  • Secret-bearing manifest fields such as tokens, cookies, authorization, credentials, and custom environment secrets are rejected.
  • Reports contain hashes and measurements, not command inputs or output bodies.
  • Artifact writes are restricted to explicit artifactDir, content addressed, exclusive, and verified by read-back SHA-256.

Run only trusted benchmark executables. The isolation above prevents accidental shell expansion and environment leakage; it is not an OS sandbox for malicious code.

Install in DSH

dsh plugin --profile benchmark add github:dongsheng123132/dsh-benchmark

The bundle registers:

  • dsh_benchmark_inspect — inspect protocol metadata and fingerprints without execution.
  • dsh_benchmark_run — run fixed cases and write a content-addressed report.
  • dsh_benchmark_compare — compare current and baseline reports with manifest thresholds.

MCP

.mcp.json declares a standalone stdio MCP server:

  • benchmark_manifest_lint validates an inline manifest and returns only identifiers, bounded policies and hashes of runner/case inputs.
  • benchmark_report_address recomputes the exact report SHA-256 and returns a bounded summary while rejecting raw-output and secret-bearing fields.

MCP accepts bounded inline JSON, never executes a command, and never reads or writes the filesystem. Actual benchmark execution remains available only through the workspace-bounded DSH tool and CLI surfaces.

CLI

dsh-benchmark inspect --root /workspace --manifest benchmark.json

dsh-benchmark run \
  --root /workspace \
  --manifest benchmark.json \
  --artifact-dir benchmark-artifacts

dsh-benchmark compare \
  --root /workspace \
  --manifest benchmark.json \
  --baseline benchmark-artifacts/baseline.json \
  --current benchmark-artifacts/current.json \
  --artifact-dir benchmark-comparisons

Exit code 0 means pass. 2 means a report/comparison was written but its scorer failed. 1 means a manifest or operational error.

Manifest example

examples/benchmark.example.json benchmarks a fixed JSONL runner. Run it from this repository:

node bin/dsh-benchmark.mjs run \
  --root . \
  --manifest examples/benchmark.example.json \
  --artifact-dir artifacts

Arguments and JSONL values can contain ordinary test data, but the report stores only their SHA-256 fingerprints. Do not place real secrets in a benchmark manifest.

Develop

npm test
npm run check
npm run smoke:plugin
npm run smoke:mcp
python C:/Users/ZhuanZ/.codex/skills/.system/plugin-creator/scripts/validate_plugin.py .

Requires Node.js 22+. No runtime dependency or install lifecycle script is used beyond the optional DSH tools SDK peer.

License

MIT