Replace absolute home directory prefix with ~ in skill <location> tags
injected into the system prompt. Models understand ~ expansion and the
read tool resolves it, so this is a safe, backward-compatible change.
Saves ~5-6 tokens per skill path. For a workspace with 90+ skills,
this reduces system prompt size by ~400-600 tokens.
Changes:
- Add compactSkillPaths() helper in workspace.ts
- Apply in buildWorkspaceSkillSnapshot and buildWorkspaceSkillsPrompt
- Add test for path compaction behavior
Before: /Users/alice/.bun/install/global/node_modules/openclaw/skills/github/SKILL.md
After: ~/.bun/install/global/node_modules/openclaw/skills/github/SKILL.md
* feat(skills): improve descriptions with routing logic
Apply OpenAI's recommended pattern for skill descriptions:
- Add 'Use when' conditions for clear triggering
- Add 'NOT for' negative examples to reduce misfires
- Make descriptions act as routing logic, not marketing copy
Based on: https://developers.openai.com/blog/skills-shell-tips/
Skills updated:
- coding-agent: clarify when to delegate vs direct edit
- github: add boundaries vs browser/scripting
- weather: add scope limitations
Glean reported 20% drop in skill triggering without negative
examples, recovering after adding them. This change brings
Clawdbot skills in line with that pattern.
* docs(skills): clarify routing boundaries (openclaw#14577) (thanks @DylanWoodAkers)
* docs(changelog): add PR 14577 release note (openclaw#14577) (thanks @DylanWoodAkers)
---------
Co-authored-by: ClawdBotWolf <[email protected]>
Co-authored-by: Peter Steinberger <[email protected]>
* test(whatsapp): add resolveWhatsAppOutboundTarget test suite
* style: auto-format files
* fix(test): correct mock order for invalid allowList entry test
Large images (2000px) consume excessive context tokens when sent to LLMs.
1200px provides sufficient detail for most use cases while significantly
reducing token usage.
The 5MB byte limit remains unchanged as JPEG compression at 1200px
naturally produces smaller files.
(cherry picked from commit 40182123dd2673b4b65e6846fa066380f10b781f)
* fix(gateway): avoid premature agent.wait completion on transient errors
* fix(agent): preemptively guard tool results against context overflow
* fix: harden tool-result context guard and add message_id metadata
* fix: use importOriginal in session-key mock to include DEFAULT_ACCOUNT_ID
The run.skill-filter test was mocking ../../routing/session-key.js with only
buildAgentMainSessionKey and normalizeAgentId, but the module also exports
DEFAULT_ACCOUNT_ID which is required transitively by src/web/auth-store.ts.
Switch to importOriginal pattern so all real exports are preserved alongside
the mocked functions.
* pi-runner: guard accumulated tool-result overflow in transformContext
* PI runner: compact overflowing tool-result context
* Subagent: harden tool-result context recovery
* Enhance tool-result context handling by adding support for legacy tool outputs and improving character estimation for message truncation. This includes a new function to create legacy tool results and updates to existing functions to better manage context overflow scenarios.
* Enhance iMessage handling by adding reply tag support in send functions and tests. This includes modifications to prepend or rewrite reply tags based on provided replyToId, ensuring proper message formatting for replies.
* Enhance message delivery across multiple channels by implementing sticky reply context for chunked messages. This includes preserving reply references in Discord, Telegram, and iMessage, ensuring that follow-up messages maintain their intended reply targets. Additionally, improve handling of reply tags in system prompts and tests to support consistent reply behavior.
* Enhance read tool functionality by implementing auto-paging across chunks when no explicit limit is provided, scaling output budget based on model context window. Additionally, add tests for adaptive reading behavior and capped continuation guidance for large outputs. Update related functions to support these features.
* Refine tool-result context management by stripping oversized read-tool details payloads during compaction, ensuring repeated read calls do not bypass context limits. Introduce new utility functions for handling truncation content and enhance character estimation for tool results. Add tests to validate the removal of excessive details in context overflow scenarios.
* Refine message delivery logic in Matrix and Telegram by introducing a flag to track if a text chunk was sent. This ensures that replies are only marked as delivered when a text chunk has been successfully sent, improving the accuracy of reply handling in both channels.
* fix: tighten reply threading coverage and prep fixes (#19508) (thanks @tyler6204)
resolveAutoEntries only checked a hardcoded list of providers
(openai, anthropic, google, minimax) when looking for an image model.
agents.defaults.imageModel was never consulted by the media understanding
pipeline — it was only wired into the explicit `image` tool.
Add resolveImageModelFromAgentDefaults that reads the imageModel config
(primary + fallbacks) and inserts it into the auto-discovery chain before
the hardcoded provider list. runProviderEntry already falls back to
describeImageWithModel (via pi-ai) for providers not in the media
understanding registry, so no additional provider registration is needed.
Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
(cherry picked from commit b381029ede72a57ef6d12d9413c98fa29501b797)
mac26ai