plano/TEST_COVERAGE_ANALYSIS.md

Test Coverage Analysis

Date: 2026-02-18

Executive Summary

The Plano codebase has ~370 automated tests: ~297 Rust unit tests, ~65 Python tests (29 CLI + 50 E2E + 4 archgw integration), 10 Hurl/REST manual test files, and zero JS/TS tests. Coverage is strong in the LLM translation layer (hermesllm) and behavioral signals (brightstaff/signals), moderate in state management and configuration, and weak in the WASM gateway plugins and several Python CLI modules.

Below is a detailed breakdown by component with prioritized improvement recommendations.

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1. Rust Crates (crates/)

Current State

Crate	Tests	Files With Tests	Status
hermesllm	148	21	Good — broad coverage of provider translation
brightstaff	126	11	Good — signals/state/routing well tested; handler endpoints less so
common	36	10	Moderate — core utilities covered; some gaps
prompt_gateway	4	2	Weak — WASM filter mostly untested
llm_gateway	0	0	None — WASM filter completely untested
Total	~314	44

Well-Tested Areas

• hermesllm provider translation (148 tests): Request/response transforms for all providers (OpenAI, Anthropic, Bedrock, Gemini, Mistral) are thoroughly tested. Streaming response parsing (20 tests), endpoint resolution (11 tests), request generation (16 tests), and cross-provider format conversion (~45 tests) are solid.
• hermesllm streaming buffers (12 tests): SSE chunk processor (6 tests), Anthropic streaming buffer (3 tests), Responses API streaming buffer (2 tests), and passthrough buffer (1 test) have coverage.
• brightstaff signals/analyzer (48 tests): Character n-gram similarity, token cosine similarity, layered matching, frustration/escalation/positive-feedback detection are thoroughly tested.
• brightstaff state management (26 tests): In-memory state (16 tests) and PostgreSQL persistence (10 tests) have good unit test coverage.
• brightstaff function calling (17 tests): Tool extraction, JSON fixing, hallucination detection, and tool call verification are well covered.
• brightstaff routing models (17 tests): Orchestrator model v1 (9 tests) and router model v1 (8 tests) are tested.
• brightstaff pipeline processor (5 tests): Has basic test coverage (4 tokio::test + 1 sync test).
• brightstaff agent selector (5 tests): Listener lookup and agent map creation are tested.
• brightstaff response handler (5 tests): Response transformation has tests.
• common rate limiting (8 tests): Rate limit logic with token quotas and header-based selectors is tested.
• common OpenAI API (9 tests): Chat completion parsing and request conversions covered.

Gaps and Recommendations

Gap 1: llm_gateway crate — 0 tests (1,399 LOC)

This WASM filter handles all LLM request/response processing and streaming. stream_context.rs (~1,000 lines) manages streaming chunk assembly and response forwarding with zero coverage.

Recommendation: Extract core logic from the WASM host context into pure, testable functions. Test streaming chunk reassembly, header manipulation, error response construction, and the filter lifecycle. Consider a thin WASM shim over well-tested logic modules.

Gap 2: prompt_gateway crate — 4 tests (1,717 LOC)

The WASM prompt filter has tests only in tools.rs (3 tests) and stream_context.rs (1 test). The filter/HTTP context lifecycle (filter_context.rs, http_context.rs), prompt guard logic, and metrics collection are untested.

Recommendation: Add tests for intent matching and prompt guard/jailbreak detection in stream_context.rs. Test http_context.rs request parsing and response construction. Same architectural approach as llm_gateway — separate testable logic from WASM host bindings.

Gap 3: brightstaff handler endpoints — limited coverage

Several handler modules have no unit tests:

• handlers/llm.rs (553 LOC) — LLM chat handler
• handlers/agent_chat_completions.rs (418 LOC) — Multi-agent orchestration
• handlers/router_chat.rs (159 LOC) — Router endpoint
• handlers/utils.rs (288 LOC) — Handler utilities

The pipeline_processor has only 5 tests for 834 LOC — basic flow is covered but error paths and edge cases are not.

Recommendation: Add tests for error paths in pipeline_processor.rs (malformed requests, downstream failures, timeout handling). Add handler-level tests for llm.rs and agent_chat_completions.rs using mockito (already a dev dependency) to mock HTTP backends.

Gap 4: hermesllm streaming transforms — 0 tests

While the streaming buffers (SSE parser, Anthropic buffer, etc.) have tests, the streaming transform modules that convert between formats during streaming are untested:

• transforms/response_streaming/to_openai_streaming.rs
• transforms/response_streaming/to_anthropic_streaming.rs

Also untested: apis/streaming_shapes/amazon_bedrock_binary_frame.rs (AWS Event Stream binary decoding) and apis/streaming_shapes/chat_completions_streaming_buffer.rs.

Recommendation: Add tests for the streaming transform modules. The Bedrock binary frame decoder is particularly important — it parses a proprietary binary protocol and failures here are hard to diagnose in production.

Gap 5: common utility modules — no tests

Several common modules lack tests:

• routing.rs — Provider routing logic
• errors.rs — Error types (ClientError, ServerError)
• http.rs — HTTP utilities and CallArgs
• stats.rs — Metrics traits
• api/prompt_guard.rs — Prompt guard types
• api/zero_shot.rs — Zero-shot classification types

Recommendation: Add tests for routing.rs (routing decisions), http.rs (CallArgs construction, URL handling), and prompt_guard.rs (guard rule evaluation). The error/stats/consts modules are mostly type definitions and don't need extensive testing.

Gap 6: brightstaff state — edge cases

The state backends have solid basic coverage (26 tests total), but lack tests for:

• Concurrent access patterns
• State expiration/eviction
• Connection failure recovery (PostgreSQL)
• Large conversation histories

Recommendation: Add tokio::test cases for concurrent read/write scenarios in the memory backend and connection pool behavior in the PostgreSQL backend.

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2. Python CLI (cli/)

Current State

Test File	Tests	Modules Covered
test_config_generator.py	11 (5 functions + 6 parametrized)	config_generator, utils
test_version_check.py	18 (4 classes, 18 methods)	versioning
test_init.py	4	init_cmd
test_trace_cmd.py	2	trace_cmd (minimal)
Total	35 executions	5 of 13 modules

Well-Tested Areas

• versioning.py (18 tests): Version parsing, comparison, PyPI fetching, network error handling, and environment variable overrides are thoroughly tested across 4 test classes.
• config_generator.py (11 tests): Happy-path config validation, schema validation errors (6 parametrized cases), and legacy format conversion are covered.
• init_cmd.py (4 tests): Clean init, template init, overwrite protection, and force overwrite are tested.

Gaps and Recommendations

Gap 7: main.py — 0 tests (441 LOC)

The CLI entry point defines all Click commands (up, down, build, logs, cli_agent, generate_prompt_targets). None have tests. The up command has complex logic for port conflict detection, API key validation, and container orchestration.

Recommendation: Add tests using Click's CliRunner. Test planoai up with mocked Docker calls (validate argument handling, port conflict error messages, API key resolution). Test planoai down and planoai build for basic argument handling and error paths.

Gap 8: targets.py — 0 tests (365 LOC)

AST-based Python code parser that extracts prompt targets from Flask/FastAPI routes and Pydantic models. This is complex parsing logic prone to edge cases with decorators, type annotations, and docstrings.

Recommendation: Create test fixtures with sample Flask/FastAPI app files and verify extracted prompt targets. Test edge cases: nested decorators, complex type hints (Optional, Union, List[dict]), missing docstrings, and unsupported patterns.

Gap 9: core.py and docker_cli.py — 0 tests (377 LOC combined)

Container lifecycle management and Docker subprocess wrappers are untested.

Recommendation: Mock subprocess.run / subprocess.Popen and test the health check retry loop, container state transitions, and error handling. A shared conftest.py with Docker mock fixtures would benefit multiple test files.

Gap 10: trace_cmd.py — 2 tests for 993 LOC

Only gRPC bind error handling is tested. Trace collection, OTEL span processing, and trace analysis logic (the bulk of the module) are untested.

Recommendation: Add tests for trace data parsing and the analysis/summarization logic. Mock gRPC server interactions for collection tests.

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3. JavaScript/TypeScript (apps/, packages/)

Current State

Zero test files. No test framework configured. The codebase has 70+ TypeScript/React source files across two Next.js apps and shared packages. Quality tooling is limited to type checking and Biome linting.

Recommendations

Gap 11: No test infrastructure

Recommendation: Set up Vitest in the Turbo workspace. Add @testing-library/react for component testing. Priority candidates:

• apps/www/src/utils/asciiBuilder.ts (425 lines of pure utility functions — ideal for unit tests)
• packages/ui/src/ (shared UI components reused across apps)

Note: These are marketing websites, not the core proxy. Prioritize this lower than Rust and Python testing.

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4. E2E and Integration Tests (tests/)

Current State

Suite	Tests	Coverage
tests/e2e/test_prompt_gateway.py	12	Prompt routing, guardrails, cross-provider SDK compatibility
tests/e2e/test_model_alias_routing.py	19	Model aliases, format translation, streaming, error handling
tests/e2e/test_openai_responses_api_client.py	17	Responses API across all providers (passthrough, chat completions, Bedrock, Anthropic)
tests/e2e/test_openai_responses_api_client_with_state.py	2	Multi-turn conversation state (memory backend)
tests/archgw/test_prompt_gateway.py	3	Prompt gateway with mock HTTP server (including 404/500 errors)
tests/archgw/test_llm_gateway.py	1	LLM gateway with provider hints
Total	54

Additional manual tests: 3 Hurl files and 6 REST files for exploratory/manual testing.

Well-Tested Areas

• Cross-provider format translation: OpenAI client → Claude model, Anthropic client → OpenAI model, etc. covered via model alias routing tests.
• OpenAI Responses API: Comprehensive coverage across all 4 providers in both streaming and non-streaming modes, with and without tools.
• Prompt gateway routing: Intent matching, parameter gathering, default targets, and jailbreak detection tested end-to-end.
• Error handling basics: 400 errors with invalid aliases, nonexistent aliases, and unsupported parameters.
• archgw mock-server tests: 404 and 500 upstream error handling tested with pytest_httpserver.

Gaps and Recommendations

Gap 12: Error and failure scenarios underrepresented

Only a few tests cover error paths. Missing scenarios:

• Upstream provider timeouts
• 5xx errors from LLM providers during streaming
• Malformed/incomplete streaming responses
• Rate limiting behavior end-to-end
• Invalid or expired API keys

Recommendation: Add E2E error scenario tests. Use a mock upstream that returns errors/timeouts to test resilience behavior without depending on real provider availability.

Gap 13: Bedrock tests unreliable

Several AWS Bedrock tests are marked as skipped/unreliable, reducing coverage of this provider path.

Recommendation: Add a mock Bedrock endpoint (or use the archgw mock server pattern from tests/archgw/) that returns Bedrock-formatted responses including the binary event stream format. This would make Bedrock tests deterministic.

Gap 14: PostgreSQL state storage not E2E tested

State management E2E tests only use the memory backend. PostgreSQL is the production persistence backend.

Recommendation: Add a PostgreSQL container to the E2E Docker Compose setup and add tests for multi-turn state persistence, session retrieval, and cleanup.

Gap 15: No concurrent request / load tests

There are no tests for behavior under concurrent requests or verifying proper resource cleanup.

Recommendation: Add parallel request tests using pytest-xdist (already in dependencies) or asyncio.gather. Test for race conditions in state writes and resource cleanup.

Gap 16: No configuration validation E2E tests

Invalid configs, missing required fields, and misconfigured providers are not tested end-to-end.

Recommendation: Add tests that pass intentionally invalid configs to planoai up and verify the error messages and exit behavior.

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Priority Summary

Priority	Area	Gap	Recommendation
P0	Rust: llm_gateway	0 tests, 1,399 LOC	Extract logic from WASM, add unit tests (#1)
P0	Rust: prompt_gateway	4 tests, 1,717 LOC	Test intent matching, prompt guards, filter lifecycle (#2)
P1	Rust: handler endpoints	llm.rs, agent_chat_completions.rs untested	Add handler-level tests with mockito (#3)
P1	Rust: streaming transforms	to_openai_streaming, to_anthropic_streaming, bedrock binary	Add streaming transform unit tests (#4)
P1	Rust: common utilities	routing.rs, http.rs, prompt_guard.rs	Add tests for routing decisions and HTTP utils (#5)
P1	Python: main.py	0 tests, 441 LOC	Test CLI commands with CliRunner (#7)
P1	Python: targets.py	0 tests, 365 LOC	Test AST parsing with sample app fixtures (#8)
P1	E2E: error scenarios	Few error path tests	Add timeout/5xx/rate-limit E2E tests (#12)
P2	Rust: state edge cases	No concurrent/expiration tests	Add async edge case tests (#6)
P2	Python: core.py/docker_cli.py	0 tests, 377 LOC	Mock subprocess, test lifecycle (#9)
P2	Python: trace_cmd.py	2 tests for 993 LOC	Test trace processing logic (#10)
P2	E2E: Bedrock	Tests skipped as unreliable	Use mock Bedrock endpoint (#13)
P2	E2E: PostgreSQL state	Only memory backend tested	Add PG to Docker Compose (#14)
P3	JS/TS	0 tests, no framework	Set up Vitest, test asciiBuilder.ts (#11)
P3	E2E: concurrency	No parallel request tests	Add concurrent request tests (#15)
P3	E2E: config validation	No invalid config tests	Test error handling for bad configs (#16)