dsh-data-quality

dsh-data-quality

Deterministic data profiling, cleaning, and verification for DeepSeek Harness.

• 1024 store channel: npm i -g dsh1024 once, then dsh1024 plugin --profile web add dsh-data-quality (counts toward the deepseek1024.com install ranking).

Deterministic data profiling, cleaning, and verification for DeepSeek Harness.

All computation is plain TypeScript in the harness process — the model never does the math. A ctx.dataQuality capability seam (Service Definition / local Provider / tool Consumers) exposes three model tools plus a frozen cross-plugin citation-checking contract.

English · 简体中文 · Español · Português · हिन्दी

dsh plugin --profile <name> add dsh-data-quality

📖 Ecosystem knowledge base — measured data, not marketing: plugin development guide · plugin-selection data · maintenance criteria.

Install & uninstall

dsh plugin --profile web add dsh-data-quality      # install (npm) — or the forms above
dsh plugin --profile web remove dsh-data-quality   # uninstall

⭐ 如果它帮到了你

这个插件是 DSH 插件家族的一员（95 个，全部 Apache-2.0）。如果你在用，给个 star —— 它不会解锁任何功能，但会让下一个人在搜索里更容易找到它。

English: part of a 95 plugin family for DeepSeek Harness. If it is useful, a star helps the next person find it — nothing is gated behind it.

What is dsh-data-quality?

Deterministic data profiling, cleaning, and verification for DeepSeek Harness.

The same run, animated.

Comparison

fixtures/dirty-fund-holdings.csv (10 rows x 6 columns) · 5 determinable dimensions · run locally

Compatibility

Component	Version
DeepSeek Harness	dsh-v0.2.1-alpha.1 (adapted 2026-10-04): the peer range now admits the alpha.2 line; there Session.append's third parameter exists only for surface-eligible types and is a SurfaceIntent, so the audit gate still skips and the storage-domain report stays the durable copy. Verified 2026-09-24 (dual typecheck rulers + full test suite green).
Node.js	^22.19.0 || >=24.0.0
Package manager	pnpm@11.7.0
Platform	Windows / macOS / Linux (host-only plugin)

What you get

• ctx.dataQuality service — a Cordis service other plugins may optionally consume (inject = ['dataQuality']). Besides the three dataset operations behind the tools, it implements the frozen verifyCitations(request) contract: verify that numbers/strings cited in a document match a dataset snapshot, with relative-tolerance numeric comparison and verified / mismatch / not-found / unverifiable statuses.
• data_profile tool — dataset profiling: row/column counts, inferred column types (number/date/boolean/string/empty/mixed), missing rates, unique counts, numeric distributions (min/max/mean/median/p25/p75), IQR outlier counts, mixed-type suspicion notes, and full-table sha256 content-hash duplicate detection with the duplicate rate and a bounded sample of duplicate row indexes. Adds a deterministic DAMA six-dimension scorecard (completeness, uniqueness, validity, consistency, timeliness, accuracy — accuracy is reported undetermined without a declared schema, never fabricated). Optional deterministic systematic sampling for large files.
• data_clean tool — ordered declarative cleaning rules: dedupe (by column group), fill-missing (constant/mean/median/forward), coerce-type (number/date/boolean; failures counted and set to missing), normalize-unit (e.g. 万/亿 suffixes to base units), trim, map-values (enum mapping). Returns a per-rule audit log, a pre-delivery contract validation summary (dedupe before/after, uniqueness, non-null and type regressions), and a bounded preview; writes the cleaned dataset only when outputPath is given, and never overwrites the source.
• data_verify tool — declarative verification rules: not-null, unique, range, regex, enum, cross-column (e.g. startDate < endDate), freshness (date column within N days of a reference date). Per-rule pass/fail with capped failing-row evidence; an overall failure is a normal passed: false result, not a tool error.
• data_report tool — read persisted reports back from the data_quality storage domain: by exact reportKey (path-safe validation, missing keys fail loud) or by kind (chronological listing). Returns the report envelope(s) — kind, dataset, timestamp, and the full stored report. format: html renders one profile/clean report as a self-contained offline HTML document (inline CSS/JS, no external requests) with the DAMA six-dimension scorecard and the profile/cleaning summary tables.
• Durable reports — every profile/clean/verify/citation run persists to the data_quality storage domain (JSON backend), keyed by run timestamp plus a dataset-path fingerprint; the key is returned as reportKey in tool results. Clean reports also persist the bounded preview and the contract summary, so every model-visible result is reconstructable from its reportKey; each clean run additionally persists a clean-diff before/after profile report.
• Session events — on hosts that can carry them safely, runs append data-quality/profile / data-quality/clean / data-quality/verify events (with the ignorable marker where supported). On the published 0.1.7-rc.2 line (as on earlier rc lines) the append is skipped by design — the storage-domain report is always the durable copy (see "Known limitations").

Quick start

dsh plugin --profile web add github:PerryLink/dsh-data-quality

npm channel

dsh plugin --profile web add dsh-data-quality

Tarball channel (no build permission needed)

pnpm pack                                  # produces dsh-data-quality-<version>.tgz
dsh plugin --profile web add ./dsh-data-quality-<version>.tgz

Git channel

dsh plugin --profile web add github:YOUR_ORG/dsh-data-quality#<commit-sha>

The first add fails because pnpm blocks the package's prepare build; copy the exact key pnpm printed into the profile's pnpm-workspace.yaml and re-run:

allowBuilds:
  'dsh-data-quality': true

Restart the profile after installing (bundles activate on restart). Then ask the agent, in a workspace containing a CSV:

Profile holdings.csv, then clean it by trimming whitespace, deduplicating on fund_code, and normalizing the holding_value column's 万/亿 units; finally verify fund_code is unique and not null.

Configuration

All keys are optional (defaults shown); invalid values fail loudly at load. Every key is settable from cordis.yml (the bundle ships cordis.patch.yml with the same defaults).

Key	Default	Description
enabled	true	Master switch; false mounts nothing at all.
maxRows	200000	Hard row cap per dataset load; larger inputs reject loudly (use the tool's sample parameter).
maxFileSizeMB	64	Hard file-size cap in MiB per dataset load.
defaultTolerance	1e-9	Default relative tolerance for numeric citation comparison when a citation omits tolerance.
evidenceRowLimit	20	Cap on failing-row evidence (verify) and preview rows (clean) in one result.
allowedExtensions	['.csv', '.tsv', '.json', '.jsonl']	Extensions accepted as datasets.
workspaceRoot	""	Absolute root for SERVICE-level calls (e.g. verifyCitations) that carry no session workspace; empty = the harness process launch directory. Tool calls always use the session's workspace cwd.
storeReports	true	Persist run reports to the data_quality storage domain and return reportKey.
scorecardWeights	all 1 (equal)	Per-dimension weights (completeness/uniqueness/validity/consistency/timeliness/accuracy) for the scorecard's weighted overall total; each weight must be a non-negative number.

Tools & surfaces

data_profile({ path, sample?, industryPreset? })

Profiles a workspace dataset. path is workspace-relative (.csv/.tsv/.json/.jsonl; JSON must be an array of flat objects). sample takes every ceil(N/sample)-th row for the column cards (deterministic; row counts stay exact). industryPreset (retail/saas/fund/real-estate/e-commerce/healthcare/logistics/manufacturing/energy) injects that industry's expected columns so the scorecard accuracy dimension becomes determinable; unknown ids fail loud. Returns the structured report — the duplicate rate, bounded duplicate-row indexes, numeric count/distinct distributions, file encoding (UTF-8 BOM + validity), and the weighted six-dimension DAMA scorecard — and renders a human-readable per-column summary plus scorecard.

data_clean({ path, rules, outputPath?, dryRun? })

Applies rules in array order, each seeing the previous rule's output. Rule reference:

Rule	Extra fields	Semantics
dedupe	columns?	Remove rows whose key-column values duplicate an earlier row (first kept; all columns when omitted).
fill-missing	column, strategy, value?	Fill missing cells: constant (needs value), mean/median (numeric columns), forward (previous non-missing).
coerce-type	column, to	Coerce to number/date (ISO)/boolean; failures become missing and are counted in the log.
normalize-unit	column, factors	Strip a unit suffix and multiply ({"万": 10000, "亿": 100000000}); plain numerics convert too.
trim	columns?	Trim whitespace of string cells (all columns when omitted).
map-values	column, map, else?	Exact-match mapping; unmapped values stay (keep, default) or become missing.

The source file is never overwritten. With outputPath the cleaned dataset is written there (workspace-confined, format by extension); without it the run is preview-only. With dryRun: true no file is written and nothing is persisted — the result returns the per-column cleaning plan and the expected contract/diffPreview. The result also carries a pre-delivery contract summary (dedupe before/after rows, uniqueness over the dedupe key or full rows, non-null regression for fill-missing columns, type regression for coerce-type columns, and the per-column decision trace), and a clean-diff before/after profile report is persisted to the storage domain.

data_report({ key?, kind?, format? })

Reads persisted reports back from the storage domain. Pass key (the exact reportKey a prior run returned) to fetch one report, or kind (profile/clean/clean-diff/verify/citations) to list every report of that kind chronologically; exactly one of key/kind is required. Malformed or missing keys fail loud. format: html (with key) renders the report as a self-contained offline HTML document — inline CSS/JS, no external requests, the DAMA six-dimension scorecard, and the profile/cleaning summary tables (profile/clean reports only).

data_verify({ path, rules, expectations? })

Evaluates verification rules. Rule reference:

Rule	Extra fields	Semantics
not-null	column	Fail missing cells (null/empty/whitespace).
unique	columns	Fail every row whose key combination repeats (missing participates).
range	column, min?, max?	Fail missing/unparseable cells and values outside the inclusive bounds (at least one bound required).
regex	column, pattern, flags?	Fail missing or non-matching cells (full JS regex).
enum	column, values	Fail cells whose trimmed text is not listed.
cross-column	left, op, rightColumn?, value?	Compare per row: numeric when both sides parse, dates compare as epochs, strings only for ==/!= (exactly one of rightColumn/value).
freshness	column, maxAgeDays, asOf?	Fail dates older than maxAgeDays before asOf (default: now); unparseable/missing fails.

expectations reconciles deterministic metrics against expected values: rowCount, columnSum, columnMean, uniqueCount, nullCount (each with column except rowCount, plus expected and an optional relative tolerance in [0, 1]). Each expectation yields passed plus actual/expected/tolerance; a mismatch is a normal passed: false verdict, never a tool error. Invalid metrics, missing columns, and out-of-range tolerances fail loud.

A missing cell fails every rule that reads it. Evidence is capped at evidenceRowLimit failing rows per rule.

ctx.dataQuality (for other plugins)

const result = await ctx.dataQuality.verifyCitations({
  dataset: 'holdings.csv',          // resolved against workspaceRoot
  citations: [
    { id: 'c1', path: 'rows[3].nav', value: 1.234, tolerance: 0.01 },
    { id: 'c2', path: 'summary.annualReturn', value: '12.34%' },
  ],
})
// result.results[i] = { id, status: 'verified' | 'mismatch' | 'not-found' | 'unverifiable', actual?, note? }

Locators walk the dataset document: CSV/TSV load as { columns, rows } (so rows[3].nav resolves), JSON is the parsed value, JSONL the array of parsed lines. Numbers compare with relative tolerance (|a-b| <= tolerance * max(|a|, |b|)); a CSV string cell that parses numerically compares as a number; strings compare exactly; incomparable type pairs are unverifiable. The service also exposes profileDataset / cleanDataset / verifyDataset (the same operations the tools call).

Permissions & data

• Reads workspace dataset files (allowlisted extensions only).
• Writes only: the data_clean output file (explicit outputPath, workspace-confined, never the input) and reports in the data_quality storage domain under the harness data directory.
• No network, no credentials, no external processes — all parsing and statistics are in-process TypeScript.
• Reports may contain sample cell values from your datasets (bounded by evidenceRowLimit and display truncation); the session log records tool arguments and results as usual.

Security boundaries

• Path confinement — dataset and output paths must resolve inside the session workspace (verifyCitations uses workspaceRoot); .. escapes and outside absolute paths reject, and both sides are normalized before comparison (Windows slash-safe).
• Bounded work — maxRows / maxFileSizeMB guards reject oversized inputs loudly; abort signals cancel long loads mid-stream.
• No overwrite — data_clean refuses an outputPath equal to the input path.
• Deterministic computation — same input, same output; the only clock is the one injected for freshness defaults and report timestamps.

Known limitations

• Session events are adaptive. The published 0.1.7-rc.2 line (like the earlier rc lines) has no plugin session-event registration surface and its Session.append cannot stamp the ignorable marker, so appending an unknown data-quality/* type would make the session log unreadable on restore. The plugin therefore appends only when the host knows the vocabulary or supports the ignorable append flag; on the published line the storage-domain report is the durable record.
• CSV dialect — comma/tab with RFC-4180 quoting, header row required, blank lines skipped, no delimiter auto-detection or comment lines.
• Type parsing is strict — numbers have no thousands separators; dates are YYYY-MM-DD / YYYY/MM/DD / ISO-like datetimes (UTC); booleans are true/false/yes/no/1/0. Everything else profiles as string/mixed — clean it with coerce-type when intended.
• JSON must be tabular for the tools (array of flat objects); verifyCitations walks arbitrary JSON documents.
• No ML anomaly detection, no PII masking, no databases, no SQL — rule-based suspicion notes only.

Development

pnpm install
pnpm run typecheck && pnpm run typecheck:ci && pnpm run typecheck:checkout && pnpm test && pnpm run build
pnpm run verify:self-contained && pnpm run verify:artifacts && pnpm run verify:readme-sync && pnpm pack

• Tests run vitest against the REAL Context/Session/ToolRuntime/storage domain from the 0.1.7-rc.2 peers (no hand-written service mocks) plus pure engine specs; every clean/verify rule has positive and negative cases, and verifyCitations covers all four statuses.
• scripts/loader-runner.mjs boots the real Loader composition and executes the profile → clean → verify chain against fixtures/ without an API key.
• Release: node scripts/release.mjs <x.y.z> (never pushes; the tag triggers release.yml).

Topics

dsh · dsh-plugin · deepseek-harness · cordis · data-quality · data-cleaning · data-profiling · data-verification

Contributors

Thanks to everyone who has shaped this plugin.

• PerryLink — maintenance and releases (0.1.2/0.1.3), peer-dependency upgrades, the npm version/downloads/CI badges, and recent fixes.
• dsh-data-quality contributors — the initial scaffold, the ctx.dataQuality seam and frozen verifyCitations contract, the deterministic dataset layer and pure engines, the data_quality storage-domain reports, the real-service vitest suite, the CI/compat/release workflows, and the five-language READMEs.

This repository has no public issue or pull request history yet; individual PR/issue numbers will be credited here as they arrive.

PerryLink DSH Plugin Family

This project is one of the 87 actively maintained DeepSeek Harness plugins from PerryLink. The family roster is 95 plugins in total — 5 frozen, 3 retired — and stays collapsed below so every README keeps a short first screen. Expand it to see every row, with the reason in the Status column.

Expand all 95 plugins

Plugin	One-liner	Status
dsh-aqua-input-check	水产养殖投入品记录核对（按投入品用量、休药期与起捕间隔核对记录自洽，仅提示差异，不作出定性结论）
dsh-archive-check	档案归档完整性与保管期限核对（依据《档案法》及配套规定，仅提示差异，不作出定性结论）
dsh-auto-review	Second-model auto-review on the approval chain, fail-closed by default
dsh-autotier	Automatic strong/cheap model-tier routing with deterministic risk guards and a /tier command
dsh-background-agents	Durable background child agents with a Web UI sidebar, messaging and interrupt	🚫 RETIRED — see the repo README
dsh-bid-ca-precheck	投标文件符合性预检（按招标文件逐条核对响应情况，仅提示差异，不作出定性结论）
dsh-bid-qual-check	投标人资格条件核对（按资格条件与证明材料核对逐条响应，仅提示差异，不作出定性结论）
dsh-budget	Cost governance for DeepSeek Harness: budgets, carbon, and latency in one panel.	🧊 FROZEN — see the repo README
dsh-cert-mcp	Read-only MCP server exposing the certification registry: grades, snapshots and five-dimension evidence
dsh-checkpoint-rewind	Claude Code /rewind-equivalent: snapshots, session forks, one-shot restore
dsh-claude-move	Migrate Claude Code sessions, memory, skills and CLAUDE.md into DSH	🧊 FROZEN — see the repo README
dsh-click	Cross-platform native desktop control for DeepSeek Harness — Windows first.
dsh-composer-history	Terminal-style input history for the web composer: arrows, Ctrl+R search
dsh-contract-stance	合同条款立场台账核对（按立场、风险等级与退让底线核对台账自洽，仅提示差异，不作出定性结论）
dsh-customs-doc-check	报关单证一致性核对（按公开的报关单填制规范核对单证间字段一致性，仅提示差异，不作出定性结论）
dsh-data-quality	Dataset quality checks and citation cross-checks (the optional numeric bridge consumed here)
dsh-defend	Prompt-injection, jailbreak, and secret-leak defense for DeepSeek Harness.	🧊 FROZEN — see the repo README
dsh-demurrage-ledger	滞箱费台账核对（按免箱期与费率核对超期天数与金额的自洽性，仅提示差异，不作出定性结论）
dsh-doublecheck	Engineering-discipline guard: requirements grill, test gates, adversary review
dsh-draw	Unified static-image generation routing for DeepSeek Harness.	🧊 FROZEN — see the repo README
dsh-drill-script-check	应急演练脚本核对（按阶段、响应分级、指挥与资源要素核对脚本齐备，仅提示差异，不作出定性结论）
dsh-eia-guide-check	环评导则适用性核对（按要素、导则名称与执行标准核对台账自洽，仅提示差异，不作出定性结论）
dsh-emergency-plan	应急预案要素齐备性与条款级页码定位（依据 GB/T 29639-2020 等公开文件，仅提示差异，不作出定性结论）
dsh-essay-rubric-check	作文量表评分核对（按评分项、原文定位与分值算术核对评分自洽，仅提示差异，不作出定性结论）
dsh-evidence-check	证据清单齐备性核对（按待证事实与证据要素核对清单自洽，仅提示差异，不作出定性结论）
dsh-export-ctl-check	出口管制物项核对（按管制清单、最终用途与许可证核对台账齐备，仅提示差异，不作出定性结论）
dsh-fast	Read-only performance diagnostics for DeepSeek Harness.
dsh-fmea-table-check	FMEA 分析表要素齐备性与风险顺序数一致性核对（按公开的 FMEA 方法标准核对表内自洽，仅提示差异，不作出定性结论）
dsh-forecast-penalty	预测准确率考核核对（按准确率、门槛与考核单价核对考核费用的算术自洽，仅提示差异，不作出定性结论）
dsh-fund-research	Deterministic research reports for Chinese public mutual funds
dsh-github	GitHub PR/issues integration for DSH, every write gated by approval
dsh-gongwen-flow-check	公文流转与办理时限核对（按公开的公文处理规范核对环节完整性与时限，仅提示差异，不作出定性结论）
dsh-gongwen-word-check	公文格式要素核对（按公开的党政机关公文格式标准核对版头与主体要素，仅提示差异，不作出定性结论）
dsh-guard-plan-qc	劳动保护与安全防护用品配置表核对（按公开的配备标准核对品名规格与配置数量，仅提示差异，不作出定性结论）
dsh-hazchem-check	危险化学品临界量与重大危险源辨识核对（按储存量与临界量核对台账自洽，仅提示差异，不作出定性结论）
dsh-hazplan-check	HAZOP 分析表要素齐备性与偏差推导一致性核对（依据公开的危险与可操作性分析标准，仅提示差异，不作出定性结论）
dsh-hidden-risk-map	安全隐患台账→《工贸企业重大事故隐患判定标准》（应急管理部令第10号）条款映射提示（仅提示差异，不作出定性结论）
dsh-hs-classify	商品归类层级一致性核对（按章、品目、子目与商品编号的层级关系核对自洽，仅提示差异，不作出定性结论）
dsh-icd-rule-check	ICD 合并编码与星剑号配对提示（依据 GB/T 14396-2016 与公开的 ICD 使用说明，仅提示差异，不作出定性结论）
dsh-industry-research	Industry research orchestration that seals its deliverables through this plugin's ctx.researchReport.assemble
dsh-lawcite-adapter	法条引用与文书要素核对（按名称、条号、原文与效力状态核对引用可核验性，仅提示差异，不作出定性结论）
dsh-laya	Laya typed decisions (noul/choice/score) as a first-class Cordis service and model-visible tools
dsh-lc-doc-check	信用证单据条款核对（按单据种类、份数、期限与不符点核对交单自洽，仅提示差异，不作出定性结论）
dsh-learning-gap-check	能力差距与培养计划核对（按能力等级差、培养措施与完成期限核对台账闭环，仅提示差异，不作出定性结论）
dsh-library	Local document knowledge base for DeepSeek Harness.
dsh-local-ai	Local-model (Ollama) integration for DeepSeek Harness.
dsh-lsp-actions	LSP diagnostics, formatting, completion, code actions and rename over language servers
dsh-mask	PII masking middleware: anonymize at the model boundary, restore at the display layer
dsh-mcp-panel	Read-only MCP runtime panel: /mcp command + Settings tab with status, tools and errors
dsh-medrec-qc	病案首页形式质控与逻辑矛盾提示（依据国卫办医发〔2016〕24号等公开文件，仅提示差异，不作出定性结论）
dsh-memento	Approval-gated cross-session memory: ctx.memory seam + SQLite + memory tool
dsh-nsfc-form-check	国家自然科学基金申请书形式审查与匿名化提示（依据《国家自然科学基金条例》与申请人导入的当年指南，仅提示差异，不作出定性结论）
dsh-nurse-record-check	护理记录时限、签名与评估表完整性校验（依据《病历书写基本规范》等公开文件，仅提示差异，不作出定性结论）
dsh-observe	OpenTelemetry and Langfuse observability exporter for DeepSeek Harness.
dsh-origin-rvc-check	原产地区域价值成分核对（按 RVC 定义式与门槛核对原产地判定自洽，仅提示差异，不作出定性结论）
dsh-ota-review-check	在线点评回复台账核对（按回复时限、问题分类与整改状态核对台账闭环，仅提示差异，不作出定性结论）
dsh-output-styles	Claude Code outputStyles-equivalent runtime style switching
dsh-paper-doc-adapter	试卷解析结构核对（按题型、答案、分值与 yotta 标识核对试卷结构自洽，仅提示差异，不作出定性结论）
dsh-permission-rules	Claude Code-style declarative allow/deny/ask permission rules with audit
dsh-permit-report-check	行政许可办理核对（按申请材料、法定时限与决定记录核对台账闭环，仅提示差异，不作出定性结论）
dsh-pipeline-check	项目全流程文件链条核对（按环节先后与金额口径核对链条自洽，仅提示差异，不作出定性结论）
dsh-pleading-draft	起诉状要素齐备性核对（按诉请、事实、证据、法条四要素核对文书齐备，仅提示差异，不作出定性结论）
dsh-plugin-doctor	Zero-dependency static + sandbox smoke detector for DSH plugins
dsh-plugin-guide	Plugin-development knowledge base as an on-demand agent skill
dsh-plugin-kit	Shared zero-runtime-dependency toolkit for the PerryLink DSH plugins
dsh-plugin-upgrade	One-package, one-corridor-index plugin upgrade skill: routes a repository to the matching closed corridor card
dsh-policy-brief-draft	政策专报要素核对（按观点、依据、出处与建议核对专报齐备，仅提示差异，不作出定性结论）
dsh-power-loss-split	线损电量拆分与考核表核对（依据公开的线损计算口径，仅提示差异，不作出定性结论）
dsh-power-ticket-check	电力工作票要素齐备性与签发许可顺序核对（依据现行电力安全工作规程，仅提示差异，不作出定性结论）
dsh-ppap-check	PPAP 提交要素齐备性核对（按公开的 PPAP 手册与提交等级核对要素齐备与版本填写，仅提示差异，不作出定性结论）
dsh-protest-deadline	质疑与投诉期限核对（按公开的政府采购质疑投诉规定核对期限与台账自洽，仅提示差异，不作出定性结论）
dsh-railway-window	铁路施工天窗台账核对（按时间窗、时长算术与命令号核对台账自洽，仅提示差异，不作出定性结论）
dsh-reach	Multi-channel approval/question bridge: WeChat/Telegram/Feishu, session console	🧊 FROZEN — see the repo README
dsh-repair-order-qc	维修工单结算核对（按项目金额、配件工时合计与结算总额核对算术自洽，仅提示差异，不作出定性结论）
dsh-research-report	Verifiable research-report engine: content-addressed evidence ledger and sealed versions
dsh-review-reply-check	审稿意见逐条回应覆盖核对（按意见与回应一一对应核对覆盖完整性，仅提示差异，不作出定性结论）
dsh-rulefile-check	规则库文件自检核对（按条款引用纪律与效力上限核对规则库自身合规，仅提示差异，不作出定性结论）
dsh-safety-brief-check	安全技术交底记录要素齐备性与签字闭环核对（依据公开的安全生产法规与检查标准，仅提示差异，不作出定性结论）
dsh-score	Multi-dimensional quality scoring for DeepSeek Harness plugins.
dsh-session-pin	Pin sessions in the Web sidebar with durable ordering	🚫 RETIRED — see the repo README
dsh-session-sync	Cross-device session sync for DeepSeek Harness — a dedicated git mirror of your session store.
dsh-site-log-check	监理日志跨日连续性与旁站覆盖提示（依据 GB/T 50319-2013 等公开文件，仅提示差异，不作出定性结论）
dsh-skill-pack-security	Security-audit skill pack: secret scan, dependency and supply-chain review
dsh-soe-decision-check	三重一大决策台账核对（按前置研究、会议审议与决议记录核对程序留痕，仅提示差异，不作出定性结论）
dsh-soilwater-check	土壤与地下水监测台账核对（按点位、监测项目、限值与超标判定核对台账自洽，仅提示差异，不作出定性结论）
dsh-sop-sync-check	作业规程与 FMEA／控制计划一致性核对（按编号与版本核对三份文件是否同步，仅提示差异，不作出定性结论）
dsh-spc-gbt-adapter	控制图常数与过程能力指数核对（按 GB/T 4091 的常规控制图常数表核对控制限与 Cp/Cpk 的自洽性，仅提示差异，不作出定性结论）
dsh-talk	Voice-first session loop for DeepSeek Harness: talk to it, hear it answer.
dsh-team-rooms	Cross-session team rooms: shared message bus, task board and timeline	🚫 RETIRED — see the repo README
dsh-tender-extract	招标文件条款摘录核对（按出处与原文逐字核对摘录完整性，仅提示差异，不作出定性结论）
dsh-tender-matrix	评标因素评分矩阵核对（按分值上限与合计核对矩阵自洽，仅提示差异，不作出定性结论）
dsh-test-drive	Isolated install-and-smoke test drives for DeepSeek Harness plugins.
dsh-ticktick	TickTick/Dida365 task bridge: session-header panel + 11 tools
dsh-translate	Vendor parameter translation and deterministic JSON repair for DeepSeek Harness.
dsh-warranty-calc	质保期与索赔金额核对（按质保期月数与里程、索赔金额算式核对自洽，仅提示差异，不作出定性结论）