Hashloom

io.github.davet47由 GitHub 帳號 davet47 發布v0.6.0更新於 Oct 24, 2026

Content-addressed contracts and a verification cache that cut agent context by skipping proven code.

概覽

AI 產生的概覽

Hashloom 把軟體單元當成內容尋址的契約提供給 AI 助理,提供精簡的上下文包、快取式測試驗證與精確的影響範圍查詢。

可以做什麼
  • 讀取某個單元的契約,取得含雜湊、相依簽章與呼叫端的精簡上下文包
  • 寫入或更新契約,回傳新雜湊、語意差異以及所有被失效的相依單元
  • 查詢影響範圍,支援直接或遞移相依,並標記尚未審查的契約
  • 依單元執行快取驗證,可擴展到完整影響範圍,僅在快取未命中時執行測試
  • 回報待處理契約、過期驗證、快取命中率與 token 計數
適用情境
適合規格驅動或契約優先的專案:助理反覆重新產生程式碼並重讀整個檔案,且每一輪都重跑相同測試所費不貲。也適合希望以機制而非慣例找出失效的相依單元,並在 CI 與開發機之間共用驗證快取的團隊。
執行需求
以 Python 套件形式透過 stdio 在本機執行(uvx 或 pip 安裝),以 hashloom serve 啟動。專案需先由 hashloom init 建立 .hashloom/ 與 contracts/ 下的 YAML 契約,並以 hashloom index 建立索引。驗證需要專案本身的工具鏈:Python,或 Go、Node 22.6 以上(TypeScript)、含 Maven 或 Gradle 的 JDK(Java)、.NET SDK 8 以上(C#)。選用的共用快取後端需要 URL 與權杖。
安裝前請注意
此伺服器會把契約檔寫入專案並執行專案的測試套件,也就是在本機執行程式碼。共用快取後端需設定 URL 與權杖,發布權杖可寫入快取的通過結果。快取通過假設測試具確定性,依賴時間、網路或隨機性的通過結果可能超出其成立條件,測試匯入的輔助函式不在雜湊範圍內。錯誤的契約比沒有契約更糟,因為助理會依它重新產生程式碼。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Hashloom,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

hashloom

[CI]

[hashloom regenerating a unit: one ~300-token context packet plus a cached verification, instead of re-reading whole files]

Hashloom treats software units as content-addressed contracts rather than files. An MCP server that makes agent regeneration loops cheap.

Because contracts are content-addressed and dependency-aware, agents reuse verification, compute blast radius precisely, and regenerate code from a few hundred tokens of context instead of re-reading whole files. Build systems ask which files changed. Hashloom asks which software obligations changed.

The name is a coinage that says exactly what it is: a loom keyed by hashes. On a loom, the warp threads are the fixed, durable strands, and the shuttle weaves disposable weft through them. Contracts are warp. Code is weft. (Until 0.3.3 this project shipped as heddle-mcp; the engine is unchanged.)

The problem

Agents repeatedly pay to rediscover software structure. Spec-driven development tools made specs the durable artifact and code regenerable, but they run on plain files, so every regeneration loop re-derives what the project already knows:

  1. Context acquisition is expensive. Regenerating one unit means re-reading whole spec and source files: thousands of tokens to learn what a few hundred convey.
  2. Verification is uncached. Every regeneration re-runs (and re-reads the output of) the full relevant test surface, even for units whose contracts haven't changed.
  3. Blast radius is by convention, not mechanism. When a spec changes, nothing tells the agent precisely which dependents are invalidated.

The model

Hashloom treats each software unit as a content-addressed contract with explicit dependencies, not a file. A contract is a small YAML spec (signature, invariants, examples, dependency names); the implementation behind it is regenerable weft. Because every contract is hashed and its dependencies are named, the structure an agent keeps re-deriving from files becomes something hashloom computes once and serves.

Outcomes

The model buys three things, all mechanical:

  • Verification caching. A green test result is keyed on the contract, implementation, and dependency hashes, and served from cache until one of them changes. pytest runs only on a real miss.
  • Mechanical blast radius. A contract change reports the exact set of invalidated dependents, transitively and by hash, not by convention.
  • Tiny context packets. An agent regenerating a unit gets the contract, its dependencies' signatures, and its callers as one packet of a few hundred tokens, instead of the whole file closure.

The number

Same three regeneration tasks on a 20-contract sample project, once with raw file reads, once through hashloom (tiktoken cl100k, reproduce with uv run python bench/benchmark.py):

taskraw fileshashloomreduction
revenue_by_region1,9253695.2x
top_customers2,1373376.3x
revenue_by_category1,9423964.9x
total6,0041,1025.4x

Raw mode counts what a file-based agent reads per task: the unit's spec file, every transitive dep's spec file, every source module in the dep closure, the unit's test file, and the output of running the suite. It is deliberately generous to the baseline: it assumes the agent already knows the exact dependency closure, which is precisely the thing hashloom computes for you.

The same methodology sweeps every unit of all five example projects — Python, Go, TypeScript, Java, and C# — via bench/sweep.py, and works on any hashloom project including yours. Full sweeps average lower than the gate (they count the leaf types that barely benefit); the ratio tracks dependency depth, so deeper projects score higher. All the numbers, their distributions, and the honest caveats live in docs/benchmarks.md.

Quickstart

bash
pip install hashloom# or from source: pip install "git+https://github.com/davet47/hashloom"
cd your-projecthashloom init                 # creates .hashloom/ and contracts/hashloom index                # builds the store from contracts/

Point Claude Code at it:

bash
claude mcp add hashloom -- hashloom serve

(Stdio transport; the server resolves the project by walking up from its working directory to the nearest .hashloom/.)

New to the workflow? docs/getting-started.md walks through building a package contract-first with an agent — the working rules to give it, the review loop, and the verify gate.

Contracts

One YAML file per unit in contracts/. Minimal, hand-writable, hashable:

yaml
name: revenue_by_regionsignature: "(sales: list[Sale]) -> dict[Region, float]"deps: [Sale, Region]            # other contract namesinvariants:  - excludes sales where completed is false  - excludes sales with null amountexamples:  - in:  "[Sale(region='QLD', amount=10, completed=True)]"    out: "{'QLD': 10.0}"tests: [tests/test_revenue.py::test_revenue_by_region]   # pytest node IDsimpl: src/revenue.py::revenue_by_region                  # current woven weftstatus: inferred        # reverse-engineered, not yet human-reviewed; omit once confirmed

Subdirectories are namespaces: contracts/billing/invoice.yaml is the contract billing/invoice, so the same short name can live in different folders. A contract's name must match its path under contracts/.

When to write a contract

A contract belongs on a stable seam: an interface other units depend on and that you expect to outlive its current implementation. The implementation behind it is disposable weft, regenerated freely. Dropping a contract where it does not earn that place is correct use, not a failure. The failure mode is the opposite, over-pinning interiors you would happily rewrite, which turns the durable layer into busywork.

Contracts are reviewed artifacts. Authoring one is cheap and getting cheaper, so the real cost is reviewing it, not writing it. A wrong contract is worse than no contract, because the durable artifact now lies: agents will regenerate code to satisfy a spec that is itself incorrect. Review a contract the way you review an interface, not the way you skim generated code.

A contract an agent reverse-engineers from existing code can declare that it hasn't earned that review yet: status: inferred. Tools then flag — by default, never refuse — any blast-radius or verification answer that rests on it (inferred: true on dependents, an inferred list on verify results, a review queue in status). Teams that want unvetted contracts to hard-fail can opt in to strict provenance mode (.hashloom/config.json → {"strict_provenance": true}): verify then refuses such units with a structured inferred_contract error — no tests run, no verdict cached — until they're reviewed; reads and writes stay advisory so drafts can still land and be inspected. Absent means confirmed, and confirming an inferred contract after review is free: status is provenance, not meaning, so the flip invalidates nothing (under strict mode, a pre-existing green simply revives on confirm).

Hashing semantics

  • Contract hash: sha256 over a canonical form: keys sorted, whitespace normalised, comments stripped, example order preserved, dep order ignored. impl, tests, invariants, and status are excluded, so relocating files never invalidates, rewording an invariant is free, and confirming an inferred contract never invalidates anything. Invariants are documentation, not a machine obligation; the real check is the tests, whose source is in the verification key.
  • Impl hash: sha256 over the normalised AST of the implementation, so reformatting and comment edits never bust the cache. Docstrings are stripped too.
  • Verification key: (contract hash, impl hash, test-source hash, toolchain identity, transitive dep contract hashes). Hashloom caches verification results, keyed so that a change to any contract in the closure, to the implementation, to a test's own source, or to the toolchain identity forces a re-run. The identity is the toolchain version (python 3.11.7, go 1.21.5, node <v> ts <v>, java 21.0.3, dotnet 9.0.303) plus, when the project commits a dependency source at its root (uv.lock, go.sum, package-lock.json, pom.xml, ...), a deps <file>=<hash> digest of it — so a green from an environment with a different declared dependency set is never trusted, and a 3.11 pass is never served to 3.13. The grain is the committed declared set (never OS/arch — CI greens still serve every platform); a venv that disagrees with its own lockfile is outside the key, which is one of the things shared-cache revocation exists for. Failures are never served from cache. For Python, the test-source hash covers each test's fixture closure too — the fixtures it requests (arguments, usefixtures, literal getfixturevalue), autouse fixtures in scope, and fixtures of fixtures, statically resolved through the test's module and conftest chain (nearest wins) — so editing only a conftest fixture busts exactly the tests that lean on it; fixture use the static walk cannot resolve degrades to hashing the whole chain, over-busting rather than under-busting. Two caveats. A cached pass assumes deterministic tests, so a green result that depended on wall-clock time, network, or randomness can outlive the condition that made it pass. And plain helper functions a test imports and calls (and non-Python test helpers) are still outside the hash — only the fixture graph is covered (see ISSUES.md).

MCP tools (the entire surface)

tooldoes
get_contractthe ~300-token context packet: contract + hash + one-line dep signatures + caller list
put_contractvalidate, write contracts/<name>.yaml, return new hash, a semantic diff of what changed, and every invalidated dependent
get_dependentsblast-radius query, direct or transitive, names + hashes; inferred (unreviewed) contracts flagged
verifyper-unit cached-pass / pass / fail plus a top-level ok gate bit; radius=true widens each name to its full blast radius; runs tests only on cache misses; failures come back as a ≤40-token assertion summary, never a traceback; inferred contracts in the closure flagged (refused under strict provenance mode)
statusdirty contracts, stale verifications, cache hit-rate, resolved verify interpreter, cumulative token counters

Every tool returns structured errors — {"error": {"code": "unknown_dep", "message": "'Regoin' not found — nearest: 'Region'"}} — never a stack trace.

The verify interpreter

verify runs your tests with the project's own python, resolved in order: hashloom serve --python PATH → .hashloom/config.json ({"python": "..."}) → an auto-detected <project>/.venv → the interpreter running hashloom. So a globally-installed hashloom can verify a project against its own virtualenv without being installed into it; hashloom status shows which interpreter it resolved.

.hashloom/config.json also takes verify_timeout (seconds per pytest run, default 300) for suites that need longer than the default, pycache_trust (default true); set pycache_trust: false — or pass --no-pycache-trust — to clear the project's __pycache__ before each verify run, so a stale .pyc can never shadow the current source, and strict_provenance (default false) to make verify refuse units whose closure contains inferred contracts.

Beyond Python

The impl's file extension picks the language adapter — each brings a normalised-AST hasher and a test runner, so the same cosmetic-vs-meaning hashing semantics hold per language:

  • Go (.go): hashes via the stdlib go/ast, runs go test -json. Toolchain resolves like the interpreter: .hashloom/config.json {"go": "..."}, else go on PATH.
  • TypeScript (.ts/.tsx/.mts/.cts): hashes via the target project's own typescript compiler API, auto-detects the test runner from package.json (vitest / jest, else Node's built-in node:test). Needs Node

    = 22.6; config key {"node": "..."}.

  • Java (.java): hashes via a single-file javac-tree helper (JDK-only, no dependencies), auto-detects the test runner from the build manifest — pom.xml routes to Maven, build.gradle/build.gradle.kts to Gradle, and a committed mvnw/gradlew wrapper is preferred over the PATH binary. Needs a JDK >= 11 plus Maven or Gradle; config key {"java": "..."}.
  • C# (.cs): hashes via a Roslyn token-stream helper that hashloom compiles once per SDK version with the SDK's own csc against its bundled Microsoft.CodeAnalysis (no packages, no network), runs dotnet test on the root project/solution with a FullyQualifiedName~ filter (xUnit, NUnit, and MSTest all ride it). A Microsoft.Testing.Platform project (xunit v3) works too, with one caveat: dotnet test ignores the filter there, so each verify runs that project's whole suite — conservative (an unrelated failure blocks; a green still covers the contract's tests). Needs the .NET SDK >= 8; config key {"dotnet": "..."}.

Python stays the default; a project can mix languages freely.

Team-shared verification cache

By default the cache lives in your local .hashloom/store.db. Point it at a shared backend and one green verify serves the whole team — CI verifies a unit once and every teammate's agent gets cached-pass:

jsonc
// .hashloom/config.json{"shared": {"url": "https://cache.internal:8770", "token": "..."}}

Run the backend anywhere with python -m hashloom.cache_server (a small bearer-token HTTP service over a SQLite store; an operational process, not a CLI command). Auth is scoped: give the server an optional --publish-token and only holders of it can write greens (CI publishes, laptops with the read token only consume; a single token still grants both roles, as before). A read-only client can set "publish": false to skip publish requests entirely. The server handles requests concurrently, and duplicate publishes of the same verification key are no-ops (first writer wins). Only greens are published — failures never cross the boundary — and the toolchain-in-key rule above keeps a shared green sound across machines. If the shared store is unreachable, verify degrades silently to local.

CLI

hashloom init · hashloom index · hashloom serve · hashloom status · hashloom verify. The sqlite store under .hashloom/ is derived state: delete it any time and hashloom index rebuilds it from contracts/. It can't serve you stale answers either — if contracts/ on disk has drifted from the store (a git pull without a reindex), verify refuses the affected units with a structured stale_store error instead of serving verdicts keyed by old hashes, until you run hashloom index.

hashloom verify <name>… runs the same cached verification as the MCP tool from the command line and exits nonzero unless every unit is green (a failure, an unknown name, or an unverifiable unit all block) — drop it in CI or a pre-commit hook. --radius widens each name to itself plus every transitive dependent, so one command gates a change's whole blast radius: hashloom verify --radius Sale.

Try the sample project

bash
cd examples/saleshashloom init && hashloom index && hashloom serve   # then point your agent at it

20 contracts, 25 tests, dependency chains up to six contracts deep. Every example directory ships its own README with per-language run instructions.

There are counterpart examples in four other languages, each using the same init && index loop:

  • Go — examples/go-ledger: 8 contracts over a small double-entry ledger. hashloom verify --radius Entry gates the blast radius with go test under the hood. Needs a Go toolchain.
  • TypeScript — examples/ts-cart: 8 contracts over a shopping cart. Run npm install first for its typescript; verification runs on Node's built-in node:test. Needs Node >= 22.6.
  • Java — examples/java-payroll: 11 contracts over a weekly payroll run, three layers deep — records, Class.method quals, a parameterized bracket table, and a @Nested test class with dotted node ids; the shape of a Spring service layer with zero framework dependencies. hashloom verify --radius TimeSheet runs Maven under the hood. Needs a JDK >= 17 and Maven.
  • C# — examples/csharp-invoices: 11 contracts over a billing run, the Java example's three-layer shape in C# idiom — records hashed whole, Class.Method quals, an [InlineData] bracket table, and a nested test class with dotted node ids (the runtime's Outer+Inner spelling). hashloom verify --radius DiscountCents runs dotnet test under the hood. Needs the .NET SDK >= 8.

Development

bash
uv syncuv run pytest             # full suite; hash stability is the load-bearing suiteuv run python bench/benchmark.py

integrations/ holds repo-only bootstrap tooling — an importer that drafts status: inferred contracts from a graphify knowledge graph (see the sales example for the walkthrough), and a GitHub spec-kit extension (integrations/speckit-hashloom/) that wires the cache-and-gate loop into /speckit.implement — draft seam contracts per feature going in, verify --radius as the definition of done coming out. Tooling, not surface: nothing in it adds an MCP tool or CLI command.

Kept deliberately small: 5 MCP tools, 5 CLI commands, contracts as plain YAML. Everything not in this README is an issue.

License

Apache 2.0

來源:README.md,提交 88deada

工具

0
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版本歷史

1
  1. v0.6.0最新Sep 16, 2026

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