RepoImmune は、リポジトリで解決済みのバグを、コードネイティブでエビデンスに基づくチェックへと変換します。人間とコーディングエージェントの両方がクエリできます。
入力 | 処理 | 出力 |
GitHub リポジトリまたは PR の差分 | 過去の issue → 修正 → テスト → AST エビデンスを取得 | 正確な回帰箇所、ソースリンク、保護されたテスト、および過去の修正内容 |
git clone https://github.com/Alex0AI/RepoImmune.git
cd RepoImmune
python -m venv .venv
# Windows: .venv\Scripts\activate
# macOS/Linux: source .venv/bin/activate
python -m pip install -e .
repoimmune init .
repoimmune check --diff examples/reintroduce-astropy-12907.diff --memory examples/memory
repoimmune replay astropy-12907 --memory examples/memory
repoimmune report --format htmlこのデモはオフライン、キーレス、実行時依存関係なしで動作します。このチェックは、Astropy PR #12907 からの実際の過去の回帰を検出するため、意図的に終了コード 2 を返します。
Related MCP server: mcp-software-engineering-challenge
Behavior Card はチャットの要約ではありません。不変条件を、修正前/修正後のコード、AST 形式、正確なシンボル、回帰テスト、コミット、ソース URL、ライセンス、エビデンスクラス、およびオプションのリプレイカプセルに結び付けます。RepoImmune は、エビデンスチェーンが不完全な場合、マイニングされた候補の昇格を拒否します。
flowchart LR
I[Issue / report] --> B[Buggy commit]
B --> F[Failing behavior]
F --> P[Fix PR / commit]
P --> T[Regression test]
T --> S[AST + symbol change]
S --> V[Repository invariant]
V --> C[Patch immunity check]同梱の垂直スライスは、この正確なリバージョンを検出します:
- cright[-right.shape[0]:, -right.shape[1]:] = right
+ cright[-right.shape[0]:, -right.shape[1]:] = 1正確な行を報告し、全 1 のブロックが歴史的に誤りだった理由を説明し、issue/PR/マージコミットにリンクし、修正とともに追加された pytest ケースを特定します。
repoimmune init .
repoimmune mine --repo owner/project
repoimmune check --diff HEAD~1
repoimmune recall "pagination returns duplicate rows"
repoimmune explain <behavior-card-id>
repoimmune replay <capsule-id>
repoimmune report --format html
repoimmune validate <card.json>check は Markdown、JSON、または SARIF を出力します。mine は保守的な候補のみを保存します。LLM を呼び出すことはなく、タイトルだけで Behavior Card を主張することもありません。
複合 GitHub Action は、プルリクエストの差分を読み取り専用で分析し、SARIF/Markdown エビデンスをアップロードします。
stdio MCP サーバーは、6 つの構造化された読み取り専用ツールを公開します: search_past_failures、explain_code_history、check_patch_against_memory、list_invariants_for_file、get_regression_test、replay_behavior_case。
オープンな Agent Skill は、エージェントに対し、リスクのある編集の前に履歴を想起し、完了を主張する前にもう一度想起するよう求めます。コミット、プッシュ、マージ、またはテストバイパスの権限は付与しません。
静的デモ は、ログインや API キーなしで動作します。
すべての結果は、明示的に次のいずれかです:
verified: 直接リプレイされたか、一次コード/テストエビデンスで機械的に裏付けられたもの。
externally_reported: 信頼できる上流またはベンチマークの実行記録であり、ここでは再現されていないもの。
heuristic: 有用な候補または類似性シグナルであり、証明ではないもの。
inconclusive: 矛盾または不完全なエビデンス。
類似性スコアが証明として提示されることはありません。調査結果には常に、一致したコードとソースエビデンスが表示されます。
エージェント/チャットメモリ: 会話やリポジトリの事実を記憶します。RepoImmune はコード履歴をマイニングし、あらゆるエージェントセッションより長く存続する機械的なチェックを作成します。
SWE-bench: エージェントが issue を修復できるかを評価します。RepoImmune は解決済みの issue を、永続的な予防資産に変換します。
静的解析: 一般的なルールから始めます。RepoImmune は、そのリポジトリの実際の障害から、リポジトリ固有の不変条件を学習します。
テスト生成: テストを作成することがあります。RepoImmune は、レポート、バグのある/修正されたコード、テスト、不変条件の間の因果連鎖を保持します。
git blame: 誰がいつ変更したかを示します。RepoImmune は、なぜその動作が生き残らなければならないかを説明し、それをチェックできます。
エビデンスに基づく比較については、research-landscape.md を参照してください。
issue テキスト、PR コメント、コード、パッチ、リポジトリメタデータは、信頼できないデータです。RepoImmune はこれらを命令として評価することはありません。マイニングは境界付き HTTPS 応答を使用します。ref とリポジトリ名は検証されます。カプセル実行は、シェルなしの固定 argv を使用し、絶対パスとシンボリックリンクを拒否し、タイムアウトします。未知のリポジトリのインストールスクリプトやテストは、デフォルトでは実行されません。SECURITY.md と docs/threat-model.md を参照してください。
アルファ版は、Python AST と pytest エビデンスを深くサポートしています。TypeScript/TSX には、正規化された構造と呼び出し抽出のためのオプションの固定 tree-sitter アダプターがあります。JavaScript は決定論的なトークン構造を使用し、Jest/Vitest はテストエビデンスとして記録できます。プログラム全体の手続き間到達可能性、自動上流環境再構築、および広範な言語サポートはロードマップ項目です。データセット規模のカードは、リプレイされるまで externally_reported です。同梱の Astropy 垂直スライスのみが、v0.1.0 でローカル検証された動作カプセルです。
python scripts/build_research_snapshot.py --limit 500 --cards 120
python scripts/run_experiments.py
pytest
coverage run -m pytest && coverage report
ruff check . && mypy src/repoimmune公開されたすべての数値は research/results.json に再生成されます。分類と制限は、失敗または結論が出なかったケースも含めて保持されます。データの来歴は DATA_SOURCES.md、THIRD_PARTY.md、および research/data-card.md にあります。
コミットされた v0.1 スナップショットには、500 の候補、120 の Behavior Card、12 のリポジトリ、30 の軽量構造カプセルが含まれています。決定論的変異では、120/120 の正確な歴史的リバージョンと 120/120 の保護されたアサーション削除を検出しました。同一シンボルの固定形式リファクタリングでは、9/120 の誤検出 (7.5%) が発生しました。タイトル由来の検索は Recall@5/MRR 1.0/1.0 に達しましたが、これは明示的に同一ソースの配管テストです。独立したマイニング精度と管理されたエージェント A/B は、依然として結論が出ていません。
新しいマイナーまたはエビデンスソースを提案する前に、CONTRIBUTING.md、ロードマップ、および Behavior Card スキーマをお読みください。Apache-2.0 ライセンスです。
中文说明：README.zh-CN.md
check patch against memory
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only restates the tool name and gives no indication of side effects, return behavior, input expectations, or what 'memory' refers to.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is minimal but not meaningfully concise; it is under-specified. It provides no front-loaded useful content and reads as a placeholder rather than a structured tool definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no parameters and no output schema, the tool still needs context such as what 'patch' and 'memory' refer to and what the result indicates. The description is completely inadequate for an agent to select and invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. There is no parameter information missing or requiring compensation from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'check patch against memory' is a verbatim restatement of the tool name, providing no additional information about what the tool actually does. It is a tautology that fails to distinguish itself from the sibling tools such as search_past_failures or explain_code_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance whatsoever about when to use this tool versus alternatives. The description offers no context, prerequisites, or exclusions, leaving an agent to guess when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
explain code history
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description adds zero behavioral information. It does not disclose whether this is a read-only operation, how it retrieves history, what output format to expect, or any side effects. The description carries the full burden for behavioral disclosure and fails entirely.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief, but brevity here is under-specification rather than efficient conciseness. A single phrase that repeats the tool name without elaboration does not earn credit for structure; it fails to convey any substantive information while appearing to be a complete definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, no annotations, and a descriptor that is a tautology. Given its sibling tools perform distinct historical/diagnostic functions, an agent cannot determine what inputs are needed, what results to expect, or how this differs from related operations. The definition is completely inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool accepts 0 parameters, so there is nothing for the description to clarify about argument meanings. Per the baseline for 0-parameter tools, this dimension is not penalized for missing parameter documentation. The description's lack of context does not affect this score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'explain code history' is essentially a restatement of the tool name with a verb and resource, but it provides no actual explanation of what 'explain' means in this context or what 'code history' refers to. It is a tautology, not a clear statement of function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus its siblings like search_past_failures or replay_behavior_case. No context, prerequisites, or situational cues are provided. The agent is left to guess which scenario would call for explaining code history.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get regression test
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden, but it reveals nothing about behavior, side effects, return values, or error cases. It is purely a label, not a behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The text is extremely short, but this is under-specification rather than useful conciseness. It says nothing beyond the tool name and provides no structured or front-loaded information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is entirely inadequate. It does not explain what a regression test is, what the tool returns, or how it relates to the listed sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool declares zero parameters, so the baseline is 4; the description adds no parameter meaning, but there are no parameters for it to explain. The permissive additionalProperties: true schema is not clarified, but that is a minor gap with no required inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'get regression test' merely restates the tool name and adds no verb-resource detail beyond it. It does not distinguish this tool from siblings like search_past_failures or replay_behavior_case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance about when to use this tool or when to prefer a sibling. No context, conditions, or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list invariants for file
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only repeats the action 'list' and the resource 'file'. It does not mention side effects (likely read-only), error conditions, ordering, filtering, or what data is actually returned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One short sentence is concise, but this is under-specification rather than efficient brevity. The description omits essential details that an agent needs, so it does not earn credit for structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description must provide nearly all context. It fails to state how the file is selected, what invariants look like, or what a successful call returns, leaving the agent with only the tool name as guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero declared parameters, so the description cannot add parameter-level detail beyond the schema. The 100% schema coverage and empty parameter list make the missing specification less harmful, though the description does not explain how 'file' is supplied.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'list invariants for file' is a near-verbatim restatement of the tool name. It identifies the action and resource but does not clarify what 'invariants' means in this context or how it differs from the sibling tools, making it tautological rather than informative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance about when to use this tool instead of alternatives such as search_past_failures or check_patch_against_memory. There is no context, prerequisite, or exclusion information, leaving the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
replay behavior case
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It fails to state side effects, permissions, return values, or any observable behavior beyond the vague verb 'replay'. There is nothing here to inform an agent about what will happen when the tool is invoked.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three words is technically concise, but this is under-specification rather than effective structure. The description has no front-loaded action statement, no scoping, and no differentiation—it reads as a placeholder, not a deliberate, minimal definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, no parameter details, and only sibling tool names for context, the description is the sole source of guidance and it provides none. An agent cannot understand what a 'behavior case' is, what replaying entails, or what result to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the description has no parameter details to explain, and the baseline is 4. However, the schema allows additionalProperties: true, meaning arbitrary input could be passed, and the description offers no hint about what properties might be relevant. This is a minor gap given no defined parameters exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description is literally the tool name: 'replay behavior case'. It restates the name without defining the action, the resource, or the domain meaning of 'behavior case'. An agent cannot distinguish it from siblings like search_past_failures or get_regression_test.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance about when to use this tool versus alternatives, no context, and no examples. The description contains only a phrase with no actionable direction, so an agent receives zero assistance in selecting it correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search past failures
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not state whether this is a read-only query, what data it covers, what it returns, or any side effects or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but not appropriately concise; it is under-specified. It consists only of a tautological phrase that adds no actionable information for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and no usage guidance, the description is completely inadequate for an agent to decide when to invoke this tool or what behavior to expect. The tool cannot be used correctly based on the provided definition alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters for the agent to interprethysics, which matches the baseline of 4. No parameter documentation is necessary since the input schema is effectively unrestricted and empty.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'search past failures' merely restates the tool name, providing no meaningful elaboration on what constitutes a 'past failure' or what the search returns. It also offers no differentiation from sibling tools like get_regression_test or replay_behavior_case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus the sibling alternatives. There is no mention of intended scenarios, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0check_patch_against_memoryexplain_code_historyget_regression_testlist_invariants_for_filereplay_behavior_casesearch_past_failuresScored across 6 tools
Each tool targets a distinct action and resource, but some functional overlap exists: 'search_past_failures' and 'get_regression_test' both relate to historical failures, and 'explain_code_history' and 'check_patch_against_memory' both deal with stored repository memory. The descriptions are terse but generally enough to guide selection.
All tool names follow a consistent lowercase snake_case verb-first pattern: search_, explain_, check_, list_, get_, replay_. The naming style is uniform and predictable across the entire set.
Six tools is well-scoped for a specialized repository memory/invariant server. Each tool has a clear purpose, and the count feels neither thin nor bloated for the apparent domain.
The surface covers the main read/replay workflow: searching failures, explaining history, checking patches, listing invariants, and replaying test cases. The only notable gap is the lack of any tool to record or update memory/invariants, but this may be intentional if ingestion happens outside the server.
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