A fixture whose description uses a YAML folded scalar, which parses with an embedded trailing newline unless normalized before use in Markdown tables.
日本語の概要は準備中です。原文の説明を表示しています。
Scan application source, agent skills, and MCP components; run penetration tests against scoped web test deployments, validate findings, and configure scan gates. Use oma-qa for broad quality reviews and domain skills for remediation.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Run the selected security checks, retain their native evidence, independently validate candidates, and report findings and coverage on the recorded source or deployment identity.
oma-qa.oma-search.oma-architecture.oma-debug or the owning backend/frontend/mobile/infrastructure skill.target and target_type: source | skill | mcp | web_runtime; source/package paths are absolute.intent: setup | scan | diff | pentest | triage | validate | ci | troubleshoot.outputs:
- name: run
artifact: ".agents/results/security/*/run.json"
required: true
- name: findings
artifact: ".agents/results/security/*/findings.json"
required: true
- name: report
artifact: ".agents/results/security/*/report.md"
required: true
Use one unique .agents/results/security/<run-id>/ per invocation and check that directory explicitly; old matching files do not establish completion.
Keep raw outputs and logs under raw/<engine>/, verification evidence under evidence/, and stable references to native engine workspaces.
When web_runtime is selected, also require runtime.json; for ci, require gate.json.
Report confirmed findings, reviewed leads, unreviewed candidates, rejected claims, scope, skips, engine failures, budget stops, and evidence limits separately.
Load the chosen target/engine resource; load the findings contract when retaining or normalizing results.
Only load validation for triage/reproduction and CI guidance for a gate request.
Use an installed/pinned native interface; inspect its version and help before choosing flags.
Deepsec init can configure models and start AI review; do not treat it as free scaffolding or run it before the selected scope/spend is authorized.
Use native cost/duration controls verified against the installed engine; record when a hard bound cannot be enforced.
ARTEX uses a verified snapshot-specific UI/API or manual/external integration; it has no assumed scanner command.
Authorization, clarification, spend, build restrictions, and completion follow ../_shared/core/execution-policy.md.
Existing backend/scope/spend authorization persists. A key, login, or installed tool alone does not authorize paid calls or changed scope.
| Concrete target | Default engine | Alternative/additional operation |
|---|---|---|
| Application source or source diff | Deepsec | Cisco AI Deep SAST when explicitly selected or included in the authorized plan |
| Agent skill directory/package | Cisco Skill Scanner | Independent validation of candidates |
| MCP source/configuration/server | Cisco MCP Scanner | Only supported static/dynamic modes within scope |
Web test deployment (web_runtime, pentest) | ARTEX | Independent runtime replay of candidates |
| Bounded source/local reproduction | Cloudflare validation method | No external network or deployment traffic |
A general repository scan selects source; do not add skill/MCP/runtime scans by implication. A full source-plus-runtime audit includes ARTEX when a concrete web test deployment is provided; absent deployment leaves that stage pending. Use the user-named engine within its supported target/mode. No failed or empty result automatically selects another engine, model, backend, or paid analyzer. Cloudflare is a validation procedure, not evidence of superior detection accuracy. Keep its local-only proof separate from ARTEX's network-scoped runtime proof and Deepsec's static-only worker.
.deepsec/ state: preserve and resume it; never reinitialize to erase a failed or noisy run.planned and running during execution, then completed | partial | failed | skipped at final handoff; unresolved required work makes the run partial.| Failure | Recovery |
|---|---|
| Unsupported target, language, mode, or incomplete parse | Record the exact excluded/unscanned units; continue only other selected operations |
| Credentials, quota, refusal, timeout, or provider error | Save native receipts; follow the selected engine's resume procedure; preserve affected scope as unverified |
| Malformed/missing output or engine crash | Mark failed/partial with captured stderr/exit; do not create a successful empty findings result |
| Selected analyzer did not run or read the full target | Mark missing/partial coverage even when the tool exits 0 |
| New engine/backend/endpoint would change cost or scope | Reuse existing shared-policy authorization; resolve only the actual missing decision |
| No OS sandbox or trusted evidence promotion | Do not execute target-controlled code; keep the candidate's exact validation blocker |
| ARTEX snapshot/artifact, allowlist enforcement, or budget controls unavailable | Leave runtime pending/partial; do not assume an upstream image/release or substitute production |
| Runtime budget stop, unsuccessful attack, or incomplete exploration | Retain task and traffic receipts; report measured coverage and stop reason |
| Replay fails or evidence disagrees | Record the observation and counterevidence; failed reproduction alone does not refute the claim |
| Source/deployment identity changes | Preserve prior evidence; invalidate current confirmation and rerun affected checks |
completed: selected operations and required evidence review are accounted for on the recorded identity; remaining reviewed leads are explicit.partial: a selected operation, coverage unit, or required validation check remains unavailable/incomplete.failed: no usable requested scan result exists; retain failure evidence and the bounded recovery action.run.json with planned receipts before execution. For runtime, bind test URL/allowlist/accounts/effects/limits and deployment/session identity; record model/backend egress separately from target-network scope.pending_candidates.confirmed requires independent observed proof; static revalidation or ARTEX narrative alone is insufficient. Keep decisive missing facts as reviewed needs_validation leads; retain unreviewed candidates separately and mark partial coverage.run.json records targets, immutable or session identity, engine completion, scope, configuration/model/version, native exits, coverage, authorized limits, and gaps.
findings.json separates final reviewed records from pending candidates; severity, native confidence/verdict, independent validation, and reproduction are distinct.
Use validation: unreviewed | supported | refuted | inconclusive and reproduction: not_attempted | reproduced | not_reproduced | blocked.
proof_context is local_sandbox, authorized_runtime, or null when no proof occurred; status is confirmed, needs_validation, or rejected.
Assign normalized severity only to confirmed evidence; preserve engine-rated severity in provenance for every candidate.
Missing deployed revision restricts runtime proof to the observed deployment/session; it cannot confirm checked-out source or another environment.
JSON syntax/schema checks establish record format; reference/hash/identity checks and independent observed proof establish evidence. Report each check's actual result separately.
Keep raw originals unchanged and access-controlled; shared/normalized copies omit passwords, keys, cookies, authorization headers, and private user data.
resources/deepsec-setup.md (Deepsec setup or missing INFO.md).resources/deepsec-scanning.md (Deepsec source analysis).resources/deepsec-config.md (Deepsec configuration or troubleshooting).resources/deepsec-matchers.md (explicit matcher work).resources/cisco-source.md (Cisco AI Deep SAST selected).resources/skill-scanning.md (skill target selected).resources/mcp-scanning.md (MCP target selected).resources/artex.md (ARTEX or web-runtime target selected).resources/validation.md (triage/validation or candidate review).resources/findings-contract.md (results retained/normalized).resources/ci.md (CI requested).../_shared/core/execution-policy.md (scope, spend, or completion decisions).../_shared/core/context-loading.md (resource/injection decisions).まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
A fixture whose description uses a YAML folded scalar, which parses with an embedded trailing newline unless normalized before use in Markdown tables.
日本語の概要は準備中です。原文の説明を表示しています。
Draft and revise academic prose against a rubric, evidence, and citation requirements. Use for essays, reports, literature reviews, or academic style audits.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluate system boundaries and architectural tradeoffs. Use for architecture decisions, design reviews, and ADRs.
日本語の概要は準備中です。原文の説明を表示しています。
Architecture specialist for software/system design, module and service boundaries, tradeoff analysis, and stakeholder synthesis. Uses context-aware methods such as diagnostic routing, design-twice comparison, ATAM-style risk analysis, CBAM-style prioritization, and ADR-style decision records.
日本語の概要は準備中です。原文の説明を表示しています。
Implement server APIs, authentication, and application data access. Schema modeling and query tuning use oma-db.
日本語の概要は準備中です。原文の説明を表示しています。
Backend specialist for APIs, databases, authentication with clean architecture (Repository/Service/Router pattern). Use for API, endpoint, REST, database, server, migration, and auth work.
日本語の概要は準備中です。原文の説明を表示しています。