For each issue anchor present in BASE 63279301bc non-test .py and absent on HEAD, the BASE comment/docstring block was re-attached at the HEAD location of the code it explained (matched by the distinctive code line / enclosing def). Sentences already covered by an existing HEAD comment were deduped; the issue number always survives. Insert-only: no code lines changed.
* refactor(clarify): halve the schema (880->436 tok/call) — same rules, half the words
* refactor(clarify): one question field — questions[] is the only advertised shape (single = one-entry array; legacy shape stays handler-accepted)
* refactor(clarify): unadvertise per-question id — response rows already carry question text + order
The `questions` parameter had a full description, but the top-level
tool description still described three single-question modes and never
mentioned batching. The model decides how to call a tool from that
description, so it kept asking one question per call.
The description now states that 2-5 independent questions can go in
one call and that one batched call is preferred over a chain of
single-question calls. The parameter description also tells the model
to put a short batch title in the still-required top-level question.
Two schema tests pin the contract: the description names the batch
capability, and the questions parameter stays optional with the
MAX_QUESTIONS cap.
The clarify tool gets an optional questions parameter (2-5 independent
questions, issue #18450). Batch-capable platform callbacks receive the
normalized list in one call and reply with per-question answers. Legacy
callbacks are looped one question at a time. The loop stops on timeout
so the user is not asked the remaining questions after they walk away.
Locked answers survive a timeout: the result carries them plus a
timed_out flag, and unanswered entries have an empty user_response.
The single-question path is byte-identical to the previous behavior.
The clarify schema now tells the model to order choices best-first, and
mark_recommended tags element 0 with "(Recommended)" at the tool layer --
the one platform-agnostic entry point -- so CLI, TUI, desktop, and every
messaging adapter inherit the label without a copy each. Each surface
already defaults its cursor to index 0, so the recommendation is the
pre-highlighted row too.
The label is presentation only: strip_recommended takes it back off
user_response, and choices_offered reports the bare list, so the agent
never reasons about (or echoes back) a string it did not write. Typed
replies on messaging platforms match with or without the suffix.
Follow-ups to the salvaged #23768 commit, which targeted a pre-79559214
codebase:
- agent/tool_executor.py + agent/agent_runtime_helpers.py: pass
multi_select at both current clarify dispatch points (the PR's
run_agent.py edits landed on dead code paths).
- tools/clarify_tool.py: replace the broad TypeError-retry in
_invoke_callback with inspect.signature detection, so a compatible
callback that raises TypeError internally is not invoked twice
(addresses hermes-sweeper review feedback on #23768).
- tests: cover single-invocation on internal TypeError, legacy 2-arg
callbacks, **kwargs callbacks, and registry handler multi_select
pass-through (schema arg → handler → callback).
The model was enumerating options inside the question string (dead prose the UI
can't render as pickable rows). Schema description now spells out: choices[] is
REQUIRED for selectable options; question holds ONLY the question.
The Discord fix (previous commit) handles dict-shaped clarify choices at the
Discord adapter only. The same dict-repr leak originates upstream at
tools/clarify_tool.py's str(c).strip() normalization — the single
platform-agnostic point both the CLI and every gateway adapter flow through.
When an LLM emits [{"description": "..."}] instead of bare strings, str(c)
produced {'description': '...'} which leaked onto the CLI panel
(cli.py:13048/13081), was returned verbatim as the user's answer
(cli.py:11945), and hit Telegram's numbered list too.
Add _flatten_choice (same label->description->text->title unwrap as the
Discord adapter, name/value excluded, keyless dicts dropped) and apply it at
the normalization line. Fixes CLI + Telegram + all platforms at the root;
the Discord smart-truncation now operates on already-clean text.
Adds johnjacobkenny to AUTHOR_MAP for the salvaged commit.
- Add 'emoji' field to ToolEntry and 'get_emoji()' to ToolRegistry
- Add emoji= to all 50+ registry.register() calls across tool files
- Add get_tool_emoji() helper in agent/display.py with 3-tier resolution:
skin override → registry default → hardcoded fallback
- Replace hardcoded emoji maps in run_agent.py, delegate_tool.py, and
gateway/run.py with centralized get_tool_emoji() calls
- Add 'tool_emojis' field to SkinConfig so skins can override per-tool
emojis (e.g. ares skin could use swords instead of wrenches)
- Add 11 tests (5 registry emoji, 6 display/skin integration)
- Update AGENTS.md skin docs table
Based on the approach from PR #1061 by ForgingAlex (emoji centralization
in registry). This salvage fixes several issues from the original:
- Does NOT split the cronjob tool (which would crash on missing schemas)
- Does NOT change image_generate toolset/requires_env/is_async
- Does NOT delete existing tests
- Completes the centralization (gateway/run.py was missed)
- Hooks into the skin system for full customizability
- Added a new `clarify_tool` to enable the agent to ask structured multiple-choice or open-ended questions to users.
- Implemented callback functionality for user interaction, allowing the platform to handle UI presentation.
- Updated the CLI and agent to support clarify questions, including timeout handling and response management.
- Enhanced toolset definitions and requirements to include the clarify tool, ensuring availability across platforms.
