CoreRasurae d9c9b57e6e feat(ci): implement TDD bug tag quality gate for bug fix PRs
Add an automated quality gate that enforces TDD bug fix workflow rules
on pull requests. The gate parses PR descriptions for bug-closing
keywords (Closes/Fixes/Resolves #N, ISSUES CLOSED: #N), searches the
codebase for corresponding TDD tests tagged @tdd_bug_N, and verifies
that @tdd_expected_fail tags have been removed.

Key components:
- scripts/tdd_quality_gate.py: Main quality gate script with PR
  description parsing, TDD test discovery, and tag removal verification.
  All public functions validate arguments fail-fast and are statically
  typed.
- noxfile.py: New tdd_quality_gate session that reads PR_DESCRIPTION
  from the environment and runs the quality gate script.
- .forgejo/workflows/ci.yml: New tdd_quality_gate CI job that runs
  only on pull_request events, passing the PR body as PR_DESCRIPTION.
- features/tdd_quality_gate.feature: 46 Behave scenarios covering PR
  parsing, TDD test search, tag removal verification, full gate logic,
  robot diff handling, edge cases, argument validation, bool guards,
  co-located bug false-positive guard, and main() CLI entry point.
- features/steps/tdd_quality_gate_steps.py: Step definitions for all
  Behave scenarios using temporary directories for isolation.
- robot/tdd_quality_gate.robot: 15 Robot Framework integration tests
  exercising the gate end-to-end via a helper subprocess.
- robot/helper_tdd_quality_gate.py: Helper script for Robot tests with
  sentinel-based sub-commands.

Review-round fixes applied:
- check_expected_fail_removed now uses _contains_tag_token for
  word-boundary matching (avoids false positives on partial tag names)
- Diff expected-fail removal detection tracks flags at file level
  instead of per-hunk (fixes false negatives when tags span hunks)
- parse_bug_refs filters out issue number zero
- Redundant double error reporting eliminated (file-level check
  short-circuits the diff-level check)
- run_quality_gate returns (errors, bug_refs) tuple to avoid
  redundant re-parsing in main()
- Regex compilation cached via functools.lru_cache
- Nox session no longer installs the full project (stdlib only)
- CI checkout uses fetch-depth: 0 for reliable merge-base resolution

Review-round 2 fixes applied:
- _diff_has_expected_fail_removal_for_bug now requires the removed
  line to contain both the expected-fail tag and the specific bug tag
  (fixes false positives when two bugs share the same test file)
- check_expected_fail_removed error messages use the correct tag
  prefix per file type (@tdd_bug_N for .feature, tdd_bug_N for .robot)
- bool values rejected by bug-number validation guards in
  find_tdd_tests, check_expected_fail_removed, and
  _diff_has_expected_fail_removal_for_bug
- File-read error handling catches UnicodeDecodeError alongside OSError
  (root-safe unreadable-file handling via invalid-UTF-8 test fixture)
- Temp directory cleanup added to after_scenario hook in environment.py
- 8 new Behave scenarios: bool type guards (2), co-located bug
  false-positive regression (1), run_quality_gate argument validation
  (3), and main() CLI entry point exit codes (2)

Review-round 3 fixes applied:
- Synthetic PR diff helper (_default_pr_diff_for_bug_refs) now
  auto-detects .robot vs .feature file type from the temp search
  tree and generates the matching diff format (fixes under-tested
  robot-format diff code path in multi-bug integration scenarios)
- check_expected_fail_removed test step now filters files by bug
  tag via find_tdd_tests before checking (matches production path
  in run_quality_gate)
- after_scenario temp directory cleanup no longer sets
  context.temp_dir = None (fixes cleanup conflict with
  cli_init_yes_flag_steps.py cleanup functions that run after hooks)
- 2 new Behave scenarios: multi-line PR description parsing, and
  non-string pr_diff type guard for run_quality_gate

ISSUES CLOSED: #629
2026-04-27 04:04:37 +00:00
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2026-04-21 19:44:48 +00:00

CleverAgents Core

CleverAgents is a Python-first automation platform. It provides a unified agents CLI, an interactive Textual TUI, embedded runtime, and service orchestration tools while embracing modern Python tooling.

Highlights

  • Unified CLI entry points: cleveragents and agents
  • Interactive TUI (agents tui) — full-screen Textual app with multi-session tabs, persona switching, slash commands, reference picker, and context-sensitive F1 help
  • Persona system — YAML-backed personas bind actors, argument presets, and scope references to named identities; persisted in ~/.config/cleveragents/personas/
  • Session management — create, list, export, and import conversation sessions; full JSON export/import for portability; Markdown transcript export (--format md) for human-readable sharing
  • First-run experienceActorSelectionOverlay guides new users to pick an actor on first TUI launch; creates a "default" persona automatically
  • Server modeagents server connect configures a remote CleverAgents server; Kubernetes Helm chart in k8s/ for production deployment
  • A2A integration — Agent-to-Agent protocol facade wires CLI and TUI to live application services (session, plan, registry, event)
  • Permissions screen — TUI overlay for reviewing tool permission requests with unified, side-by-side, and context diff views; session-scoped allow/reject decisions
  • Actor thought blocks — expandable reasoning trace widgets rendered inline in the conversation stream with muted styling
  • UKO runtime — Universal Knowledge Ontology query interface, inference engine, and graph persistence for ACMS context strategies
  • Database resource handler — full CRUD and checkpoint/rollback support for SQLite, PostgreSQL, MySQL, and DuckDB resources
  • Estimation lifecycleactor.default.estimation config key wires an estimation actor into the Strategize-to-Estimate lifecycle hook
  • Shell danger detection — TUI shell mode (! prefix) classifies commands by danger level (LOW → CRITICAL) and surfaces a warning overlay before executing destructive, privilege-escalating, or exfiltration-risk commands
  • Inline permission questionsPermissionQuestionWidget renders single-file permission requests directly in the conversation stream with single-key shortcuts
  • Invariant reconciliationInvariantReconciliationActor runs automatically at every plan phase transition; failures block the transition and emit INVARIANT_VIOLATED
  • UKO provenance tracking — every typed triple now carries sourceResource, validFrom, and isCurrent metadata; a revision chain enables temporal queries
  • JSON-RPC 2.0 A2A wire formatA2aRequest/A2aResponse fields renamed to standard JSON-RPC 2.0 names (method, id, result, error)
  • Fast Typer/Click-based interface with parity for help/version behavior
  • Behavior-driven coverage via Behave and Robot Framework
  • Nox automation for linting, typing, testing, docs, builds, and benchmarks
  • MkDocs-powered documentation with CleverAgents branding

Quick Start

# clone the CleverAgents core repository
git clone https://git.cleverthis.com/cleveragents/core.git
cd core

# install dependencies
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev,tests,docs]"

# set up pre-commit hooks and verify tooling
bash scripts/setup-dev.sh

# verify the CLI
agents --help
agents --version

Launch the TUI

# install TUI extra
pip install -e ".[tui]"

# launch the interactive terminal UI
agents tui

Inside the TUI:

  • Type a message and press Enter to chat with the active actor
  • Press / to open the slash command overlay (67 commands across 14 groups)
  • Press @ to open the reference picker and insert file/resource references
  • Press ! to enter shell mode and run a subprocess command
  • Press F1 to toggle the context-sensitive help panel
  • Press Ctrl+T to cycle through argument presets for the active persona
  • Press Ctrl+Q to quit

Session management

agents session create --actor openai/gpt-4o
agents session list
agents session export --session-id <ID> --output session.json
agents session import --input session.json

Server mode

# connect to a remote CleverAgents server
agents server connect --url https://my-server.example.com --token <TOKEN>

# check connection status
agents server status

Developing

Pre-commit hooks run automatically on every git commit (formatting, linting, type checking, security scanning). To run checks manually:

# core validation
nox -s format            # ruff auto-formatting
nox -s lint              # ruff linting
nox -s typecheck         # pyright type checking
nox -s unit_tests        # behave unit tests
nox -s integration_tests # robot integration tests

# quality & security
nox -s security_scan     # bandit security scanning
nox -s dead_code         # vulture dead code detection
nox -s complexity        # radon complexity analysis
nox -s pre_commit        # run all pre-commit hooks
nox -s adr_compliance    # verify ADR compliance

For the full quality automation guide, see docs/development/quality-automation.md.

Documentation

nox -s docs
nox -s serve_docs

Tests

Behave feature scenarios live under features/ and Robot suites under robot/. Use the Nox sessions above to execute them in parity with the implementation plan.

Observability

LangSmith tracing is optional and off by default. Enable it by exporting CLEVERAGENTS_LANGSMITH_ENABLED=true along with a project name and API key (CLEVERAGENTS_LANGSMITH_PROJECT, CLEVERAGENTS_LANGSMITH_API_KEY). The settings module automatically mirrors these values to LANGCHAIN_TRACING_V2, LANGCHAIN_PROJECT, and LANGCHAIN_API_KEY, so LangChain/LangGraph agents emit traces without extra wiring. Additional knobs such as CLEVERAGENTS_LANGSMITH_ENDPOINT, CLEVERAGENTS_LANGSMITH_USER_ID, and CLEVERAGENTS_LANGSMITH_TAGS are documented in docs/observability.md.

LLM provider configuration

CleverAgents ships with a LangChain/LangGraph powered provider registry that discovers whichever API keys you export and automatically selects the best available provider. The CLI now uses actors: select an actor with --actor <name> (or set a default via agents actor set-default). Actors embed provider/model choices; built-in actors are seeded from CLEVERAGENTS_DEFAULT_PROVIDER / CLEVERAGENTS_DEFAULT_MODEL, then fall back to the built-in order (openai → anthropic → google → azure → openrouter → groq → together → cohere → gemini).

Required environment variables

Provider Primary variables
OpenAI OPENAI_API_KEY
Anthropic ANTHROPIC_API_KEY
Google GOOGLE_API_KEY or GOOGLE_GENAI_API_KEY
Azure OpenAI AZURE_OPENAI_API_KEY plus AZURE_OPENAI_ENDPOINT/AZURE_OPENAI_DEPLOYMENT
OpenRouter OPENROUTER_API_KEY (+ optional CLEVERAGENTS_OPENROUTER_ORGANIZATION for sanitized headers)
Gemini GEMINI_API_KEY or GOOGLE_GEMINI_API_KEY
Cohere COHERE_API_KEY
Groq GROQ_API_KEY
Together TOGETHER_API_KEY

Set CLEVERAGENTS_DEFAULT_PROVIDER to pin the global provider (for example export CLEVERAGENTS_DEFAULT_PROVIDER=openai) and CLEVERAGENTS_DEFAULT_MODEL to lock in a model ID. When unset, the registry picks the first configured provider and uses its published default model such as gpt-4o for OpenAI or claude-sonnet-4-20250514 for Anthropic.

Diagnostics and testing shortcuts

  • agents diagnostics prints whether the registry can see your credentials and which actor/provider is selected.
  • agents tell and agents build require --actor <name> unless a default actor is set; use agents actor set-default <name> to configure one.
  • Built-in actors (<provider>/<model>) are immutable, custom actors must be named local/<id>, and the default actor cannot be removed. Use --unsafe when adding/updating configs marked unsafe; runtime only warns when invoking unsafe actors.
  • CLEVERAGENTS_TESTING_USE_MOCK_AI=true forces the in-repo mock provider so Behave/Robot suites never hit external APIs.
  • The full capability matrix (streaming, tool calls, JSON mode, etc.) is documented in docs/reference/providers.md.
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