Reality Graph Verification Tools

Reviewed Jan 1, 2000.

• tools: 10 tools scanned
• metadata: scanned

No findings.

Tools (10)

• check_verification_debt

  Estimate a software team's verification debt from team parameters. Computes the four published metrics (generation-to-verification ratio, review depth, unverified-merge rate, two-week churn) and an annual cost estimate, with the full calculation path, labeled assumptions, thresholds, and sources (GitClear, Sonar, Faros, Veracode). Deterministic arithmetic from published models - no benchmark claims. Only team_size is required; every additional parameter refines the estimate. Set lang='de' for a German report.

• lint_task_spec

  Check whether a free-text work order for an AI coding agent is verifiable BEFORE handing it over. Heuristic, deterministic lint of the task's form against the four building blocks of a checkable task (goal, boundaries, acceptance criteria, validation plan) plus rule checks (vague adjectives without numbers, unnamed unhappy paths, missing file anchors). Returns a status table with evidence, the concrete questions that close each gap, and a fill-in skeleton. It checks form, not content — no LLM, nothing stored. Set lang='de' for a German report.

• get_task_contract_template

  Returns Reality Graph's free fill-in template (v0) for a verifiable task contract: goal, non-goals, boundaries (may change / must not change / forbidden), 3-7 yes/no acceptance criteria, validation plan, expected evidence, assumptions, open questions — with a filled example and fill-in guidance. Write the contract before an AI agent runs; verify the result against it after. format='json' returns a machine-fillable JSON structure; default is a compact markdown skeleton. Set lang='de' for German. Static content, nothing stored.

• validate_task_contract

  Deterministically validates a FILLED task contract (the JSON structure from get_task_contract_template): completeness of goal/non-goals/boundaries, decidability of each acceptance criterion (vague words, missing measurable markers), automated checks in the validation plan, expected evidence, and leftover placeholders. Returns a verdict (PASS / PASS WITH WARNINGS / FAIL), four dimension scores, and a concrete fix per finding. Validates form and completeness, not correctness. No LLM, nothing stored. lang='de' for German.

• get_verification_report_template

  Returns the free fill-in template (v0) for a verification report — the artifact you write right after an AI-assisted run: task recap, files changed AND files confirmed untouched, validation results per acceptance criterion (not authored by the generating model), what was skipped, limitations, and the explicit decision. format='json' for a machine-fillable structure; default is a compact markdown file. Static content, nothing stored. lang='de' for German.

• search

  Full-text search over the Reality Graph knowledge base on AI coding verification: 40+ glossary definitions, 700+ FAQ answers, sourced statistics, and article summaries on verification debt, AI code review, spec-vs-implementation checking, EU compliance (EU AI Act, GDPR, NIS2), and AI coding governance — in English and German. Returns matching documents with title, URL, and snippet. Use fetch to read a result.

• fetch

  Fetch a document from the Reality Graph knowledge base by id (as returned by search, e.g. '/verification-debt') or by full realitygraph.dev URL. Returns the document's summary, definitions, key facts, FAQ, and sources as text, plus the canonical URL.

• plan_change_verification

  Turn explicit change characteristics into a risk tier, required automated checks, manual scenarios, evidence, release blockers, role handoff, and canonical Reality Graph guidance. Use before implementation or review. It does not inspect code and never invents a confidence score.

• check_release_readiness

  Return GO, CONDITIONAL, or NO_GO from supplied acceptance-criterion results, check evidence, rollback, monitoring, limitations, and independent review. The verdict is deliberately based only on supplied evidence; this tool does not inspect code, CI, or a deployment.

• calculate_verification_capacity

  Calculate weekly review demand, utilization, capacity gap, supported change throughput, and changes lacking evidence from measured team inputs. No cost model, benchmark, or hidden industry assumption is applied; the output shows the arithmetic and a concrete balancing action.