- New crates/g3-core/src/tools/envelope.rs with execute_write_envelope()
and verify_envelope() (moved from shadow_datalog_verify in plan.rs)
- write_envelope accepts YAML facts, writes envelope.yaml to session dir,
then runs datalog verification against analysis/rulespec.yaml in shadow mode
- plan_verify() now only checks envelope existence (no longer runs datalog)
- Tool count: 13 -> 14
- Updated system prompt to instruct agents to call write_envelope before
marking last plan item done
- Updated integration tests to use write_envelope tool directly
Workflow: write_envelope -> verify_envelope -> datalog shadow artifacts
plan_write(done) -> plan_verify -> checks envelope exists
- Remove rulespec parameter from plan_write tool definition and execution
- Remove rulespec compilation from plan_approve (no longer pre-compiles)
- Remove write_rulespec, get_rulespec_path, format_rulespec_yaml/markdown
from invariants.rs; read_rulespec() now takes &Path working dir
- Remove save/load_compiled_rulespec, get_compiled_rulespec_path from datalog.rs
- Update shadow_datalog_verify() to compile on-the-fly from
analysis/rulespec.yaml, writing rulespec.compiled.dl and
datalog_evaluation.txt to session dir
- Remove rulespec display from plan_read output
- Remove Invariants/Rulespec section from native.md system prompt
- Remove rulespec from prompts.rs plan_write format and examples
- Update existing tests to remove rulespec from plan_write calls
- Add 3 integration tests for on-the-fly rulespec verification
Migrate research and research_status tools from core tools to a
dynamically loadable toolset, following the same pattern as webdriver.
Changes:
- Add 'research' toolset to TOOLSET_REGISTRY in toolsets.rs
- Add create_research_tools() function with research and research_status
- Remove research tools from create_core_tools() in tool_definitions.rs
- Remove exclude_research field and with_research_excluded() from ToolConfig
- Update tests: core tools now 13 (was 15), added 3 research toolset tests
The agent must now call load_toolset('research') to use research tools.
This simplifies the default tool set and removes special-case logic for
the scout agent (which simply won't load the research toolset).
Restores the research tool that was previously externalized as a skill:
- Add pending_research.rs: PendingResearchManager with thread-safe task tracking
- Add tools/research.rs: execute_research (async), execute_research_status
- Add research/research_status tool definitions with exclude_research config
- Integrate PendingResearchManager into Agent and ToolContext
- Inject completed research results in streaming loop
Remove research skill:
- Clear EMBEDDED_SKILLS array in embedded.rs
- Delete skills/research/ directory
- Update all tests expecting embedded research skill
- Update docs and memory to reflect the change
The research tool now:
- Spawns scout agent in background tokio task
- Returns immediately with research_id
- Automatically injects results into conversation when ready
- Supports status checks via research_status tool
Solves the tautology problem where the LLM would write invariants after
implementation, making them match what was done rather than constrain it.
Changes:
- plan_write now accepts 'rulespec' parameter
- New plans REQUIRE rulespec (fails with helpful error if missing)
- Plan updates don't require rulespec (backward compatible)
- Rulespec is parsed, validated, and written atomically with plan
- Updated system prompt with clear examples for new vs update
- Updated tool definition schema
- Updated all affected tests
New flow: task → plan+rulespec → user reviews BOTH → approve → implement
Replaces the built-in research/research_status tools with a portable
skill-based approach:
- Add embedded skills infrastructure (skills compiled into binary)
- Add repo-local skills/ directory support (highest priority)
- Create research skill with SKILL.md and g3-research shell script
- Script extraction to .g3/bin/ with version tracking
- Filesystem-based handoff via .g3/research/<id>/status.json
- Remove PendingResearchManager and all research tool code
- Update system prompt to reference skill instead of tool
Benefits:
- No special tool infrastructure needed (just shell + read_file)
- Context-efficient (reports stay on disk until needed)
- Crash-resilient (state persisted to filesystem)
- Portable (skill can be overridden per-workspace)
Breaking change: research tool calls now return a deprecation message
pointing to the research skill.
Change Plan Mode to allow multiple negative and boundary checks per item,
while keeping happy path as a single check.
Schema change:
- checks.negative: Check -> Vec<Check> (>=1 required)
- checks.boundary: Check -> Vec<Check> (>=1 required)
- checks.happy: Check (unchanged, single)
This better reflects real-world tasks where there are often multiple
error conditions and edge cases worth tracking.
Changes:
- Update Checks struct to use Vec<Check> for negative/boundary
- Update validation to require at least 1 of each
- Update prompts and tool definitions with new array syntax
- Add 4 new tests for multi-check scenarios
Plan Mode is a cognitive forcing system that requires reasoning about:
- Happy path
- Negative case
- Boundary condition
New tools:
- plan_read: Read current plan for session
- plan_write: Create/update plan with YAML content (validates structure)
- plan_approve: Mark current revision as approved
New command:
- /feature <description>: Start Plan Mode for a new feature
Plan schema requires:
- plan_id, revision, approved_revision
- items with id, description, state, touches, checks (happy/negative/boundary)
- evidence and notes required when marking items done
Verification:
- plan_verify() called automatically when all items are done/blocked
Removed:
- todo_read, todo_write tools
- todo.rs module and related tests
The research tool now spawns the scout agent in a background tokio task
and returns immediately with a research_id placeholder. This allows the
agent to continue working while research runs (30-120 seconds).
Key changes:
- New PendingResearchManager for tracking async research tasks
- research tool returns immediately with placeholder containing research_id
- research_status tool to check progress of pending research
- Auto-injection of completed research at natural break points:
- Start of each tool iteration (before LLM call)
- Before prompting user in interactive mode
- /research CLI command to list all research tasks
- Updated system prompt to explain async behavior
The agent can:
- Continue with other work while research runs
- Check status with research_status tool
- Yield turn to user if results are critical before continuing
Rename all references from "Project Memory" to "Workspace Memory" to avoid
future conflation if a "project" concept is introduced later.
Changes:
- Rename read_project_memory() -> read_workspace_memory()
- Update all prompts, tool descriptions, and comments
- Update header parsing in memory.rs to use "# Workspace Memory"
- Update display detection for "=== Workspace Memory ==="
- Update documentation and analysis/memory.md
11 files changed, ~36 occurrences updated.
LLMs were prefixing shell commands with `cd <workspace> &&` unnecessarily,
wasting tokens and cluttering CLI display. Added clear guidance in the
shell tool description that commands already execute in the working directory.
- Rename take_screenshot -> screenshot, code_coverage -> coverage (shorter names)
- Align | character across all compact tools (pad to 11 chars for str_replace)
- Make code_search a compact tool with summary display
- Show language and search name in code_search output (e.g., rust:"find structs")
- Add format_code_search_summary() to extract match/file counts from JSON response
ACD (Aggressive Context Dehydration) fixes:
- Fixed dehydrate_context() to extract turn summary from context window
instead of using the passed-in final_response (which contained only
the timing footer, not the actual LLM response)
- Removed final_response parameter from dehydrate_context() since it
now self-extracts the last assistant message as the summary
- This ensures the actual turn summary is preserved after dehydration,
not just the timing footer
New /dump command:
- Added /dump command to dump entire context window to tmp/ for debugging
- Shows message index, role, kind, content length, and full content
- Available in both console and machine modes
UTF-8 safety:
- Fixed truncate_to_word_boundary() to use character indices instead of
byte indices, preventing panics on multi-byte UTF-8 characters
- Added UTF-8 string slicing guidance to AGENTS.md
Agent: g3
- Remove IMPORTANT FOR CODING section (~1,500 chars of coding guidelines)
- Remove <use_parallel_tool_calls> block (~500 chars)
- Remove unused const_format dependency from g3-core
- Simplify get_system_prompt_for_native() to just return base prompt
- Response Guidelines now cleanly ends the static prompt
Prompt reduced from ~8,500 to ~6,500 characters.
New tool that spawns a scout agent to perform web research and return
a structured research brief. The scout agent uses webdriver to browse
the web and returns a decision-ready report.
Changes:
- Added 'research' tool definition (12 core tools total)
- Added research tool dispatch in tool_dispatch.rs
- Created tools/research.rs implementation:
- Spawns 'g3 --agent scout <query>' as subprocess
- Captures stdout and extracts last line (report file path)
- Reads and returns the report file contents
- Added exclude_research flag to ToolConfig
- Scout agent (agent_name == 'scout') does NOT have access to research
tool to prevent infinite recursion
- Updated system prompts to describe when to use research tool
- Added scout.md agent prompt with research brief output contract
The research tool is preferred for complex research tasks (APIs, SDKs,
libraries, approaches, bugs). WebDriver can still be used directly for
simple lookups or fine-grained control.
- Remove final_output from tool definitions, dispatch, and misc tools
- Update system prompts to request summaries as regular markdown text
- Remove print_final_output from UiWriter trait and all implementations
- Remove final_output handling from agent core logic
- Rename final_output_summary → summary in session continuation
- Delete final_output test files
- Update tool count tests (12→11, 27→26)
This allows LLM summaries to stream through the markdown formatter
for a more natural, responsive user experience instead of buffering
everything into a tool call.
