Plugin directory / Developer / dsh-benchmark
dsh-benchmark
Verified · install-tested on dsh dongsheng123132
What it does
A plugin in the Developer category for DeepSeek Harness.
Works — verified, early-stage project
A plugin in the Developer category for DeepSeek Harness. It installs cleanly and boots without issues in our testing. It's early-stage but functional.
“Verified” means our automated CI actually ran dsh plugin add in a clean profile and it booted — nothing more. Feature descriptions and version compatibility are the author’s claims. This is not a security audit and not an endorsement of third-party code.
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.nodemaps to the current absoluteprocess.execPath. Other executables must be explicit workspace-relative regular files; PATH lookup is not used.cwd, target files, manifests, reports, and artifact directories cannot escapeworkspaceRootthrough 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_lintvalidates an inline manifest and returns only identifiers, bounded policies and hashes of runner/case inputs.benchmark_report_addressrecomputes 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
Install
Install the catalog once, then DeepSeek Harness can find and install any plugin from this site automatically:
dsh plugin add dshbase-catalog Then say "install dsh-benchmark for me" — your agent finds it in the directory and installs it. Docs: dshbase-catalog · verified packs.
This plugin is GitHub source (not published to npm) — install it straight from the repo:
Web profile:
dsh plugin --profile web add github:dongsheng123132/dsh-benchmark Headless (CLI) profile:
dsh plugin --profile headless add github:dongsheng123132/dsh-benchmark Test report
Verified: L1 install + L2 load + L3 runtime from GitHub source on dsh 0.1.0-rc.6.
When to use it
Extend the agent's coding surface — give it a new tool, workflow, or integration so it handles a dev task it couldn't before.
Who it's for
Developers who want dsh to behave like a teammate on real codebases — editing, running, and verifying changes rather than just answering.
For developers — extending it
The tool/command surface is the seam: expose more of the SDK, add smarter context wiring, or tighten the loop between code changes and verification.