# agentassay - Doramagic AI Context Pack > Purpose: pre-work context for the user's host AI. This pack does not prove that the project has been installed, run, or validated. ## Project - canonical_name: `qualixar/agentassay` - capability: Token-efficient stochastic testing for AI agents. 5-20x cost reduction. 10 framework adapters. Paper: arXiv:2603.02601 - expected_user_outcome: Token-efficient stochastic testing for AI agents. 5-20x cost reduction. 10 framework adapters. Paper: arXiv:2603.02601 ## Operating Boundaries - Do not claim that the project has been installed, run, called through an API, or used on local files unless separate evidence proves it. - Project facts must come from repo evidence, Claim Graph, or explicit source references. - When a capability is not verified, mark it as unverified instead of completing it as fact. - publish_status: `publishable` - blocking_gaps: none --- ## Doramagic Context Augmentation The following sections strengthen the repository context for a host AI. Human Manual data is a reading route, and pitfall notes become operating constraints. ## Human Manual Outline Usage rule: this is only a reading route and salience signal, not factual authority. Concrete claims must still return to repo evidence or Claim Graph. Host AI hard rules: - Do not treat page titles, section order, summaries, or importance values as factual project evidence. - When explaining the Human Manual outline, state that it is only a reading route or salience signal. - Capability, installation, compatibility, runtime state, and risk claims must cite repo evidence, source paths, or Claim Graph. - **Introduction and Layered Architecture**: importance `high` - source_paths: README.md, pyproject.toml, src/agentassay/__init__.py, src/agentassay/core/models.py, src/agentassay/core/runner.py - **Token-Efficient Testing Pipeline and Statistical Engine**: importance `high` - source_paths: src/agentassay/efficiency/fingerprint.py, src/agentassay/efficiency/budget.py, src/agentassay/efficiency/multi_fidelity.py, src/agentassay/efficiency/warm_start.py, src/agentassay/efficiency/regression.py - **Framework Adapters, CLI, Dashboard and pytest Integration**: importance `high` - source_paths: src/agentassay/integrations/base.py, src/agentassay/integrations/custom_adapter.py, src/agentassay/integrations/langgraph_adapter.py, src/agentassay/integrations/crewai_adapter.py, src/agentassay/integrations/autogen_adapter.py - **Analysis Methods, Persistence, Reporting and Deployment Operations**: importance `high` - source_paths: src/agentassay/coverage, src/agentassay/mutation/runner.py, src/agentassay/mutation/operators.py, src/agentassay/mutation/prompt_ops.py, src/agentassay/mutation/tool_ops.py ## Repo Inspection Evidence - repo_clone_verified: true - repo_inspection_verified: true - repo_commit: `7da9a259717aee9bfb0abc40ce57b0e1df425881` - inspected_files: `README.md`, `pyproject.toml`, `docs/architecture/overview.md`, `docs/concepts/coverage.md`, `docs/concepts/mutation-testing.md`, `docs/concepts/stochastic-testing.md`, `docs/concepts/token-efficient-testing.md`, `docs/getting-started/installation.md`, `docs/getting-started/quickstart.md`, `docs/guides/adapters/autogen.md`, `docs/guides/adapters/bedrock.md`, `docs/guides/adapters/crewai.md`, `docs/guides/adapters/custom.md`, `docs/guides/adapters/langgraph.md`, `docs/guides/adapters/mcp.md`, `docs/guides/adapters/openai.md`, `docs/guides/adapters/semantic-kernel.md`, `docs/guides/adapters/smolagents.md`, `docs/guides/adapters/vertex.md`, `docs/guides/ci-cd-integration.md` Host AI hard rules: - Without repo_clone_verified=true, do not claim that the source code has been read. - Without repo_inspection_verified=true, do not write README, docs, or package-file conclusions as facts. - Without quick_start_verified=true, do not claim that the Quick Start path has run successfully. ## Doramagic Pitfall Constraints These rules come from Doramagic discovery, validation, or compilation findings. The host AI must treat them as operating constraints, not background notes. ### Constraint 1: Capability evidence risk requires verification - Trigger: README/documentation is current enough for a first validation pass. - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: capability.assumptions | https://github.com/qualixar/agentassay - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 2: Maintenance risk requires verification - Trigger: Project evidence flags a maintenance risk. Review the linked source before relying on this workflow. - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: evidence.maintainer_signals | https://github.com/qualixar/agentassay - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 3: Security or permission risk requires verification - Trigger: no_demo - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: downstream_validation.risk_items | https://github.com/qualixar/agentassay - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 4: Security or permission risk requires verification - Trigger: no_demo - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: risks.scoring_risks | https://github.com/qualixar/agentassay - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 5: Maintenance risk requires verification - Trigger: issue_or_pr_quality=unknown。 - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: evidence.maintainer_signals | https://github.com/qualixar/agentassay - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 6: Maintenance risk requires verification - Trigger: release_recency=unknown。 - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: evidence.maintainer_signals | https://github.com/qualixar/agentassay - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.