When an agent had any skill bound, the runtime tool gate was silently
hiding @Tool beans that aren't declared in any skill manifest, even
though the global system prompts (SOUL.md / "Web Search Capability" /
"File Reading Guidelines") explicitly tell the LLM these tools are
available. Result: the model would call search / renderDocx / read_file
/ etc., hit "Tool not found", then either give up or fall back to
unhelpful behaviour (e.g. dumping markdown text instead of producing a
.docx download).
This commit:
- Adds universally-promised, agent-wide tools to SYSTEM_LEVEL_TOOLS so
they bypass the manifest restriction: document/media generation
(renderDocx*, image_generate, music_generate, video_generate),
global capability tools the system prompt mentions (search,
browser_use, read_file / write_file / edit_file /
execute_shell_command, detect_file_type, extract_*_text,
readMateClawDoc), skill discovery siblings (listSkillFiles,
listAvailableSkills), and the delegate triplet (delegateToAgent,
delegateParallel, listAvailableAgents).
- Fixes 5 entries in the prior whitelist whose names did not match
any real @Tool bean and were therefore silently dead:
read_workspace_file -> read_workspace_memory_file
write_workspace_file -> write_workspace_memory_file
list_workspace_files -> list_workspace_memory_files
delegate_agent -> delegateToAgent
datetime -> getCurrentDate / getCurrentDateTime / getCurrentTime
Also adds the missing edit_workspace_memory_file.
- In the chat markdown renderer, strips any hallucinated
https?://<host> prefix from /api/v1/files/generated/<id> download
links before building the <a href>. Multiple LLMs have been
observed prepending bogus hosts when echoing tool-returned download
URLs back to the user, breaking the click. One-line defensive
normalization independent of which model is in use.
Verified end-to-end on a previously-broken agent: search / browser_use
/ execute_shell_command / renderDocx all dispatch correctly now and
the final markdown link is a clean same-origin path. 36 whitelist
entries cross-checked against real @Tool method names.
AgentBindingServiceTest green.
When a user-installed skill (e.g. RedisOps) was bound to an agent, the
model frequently called the skill name directly as a tool, hit
"Tool not found: RedisOps", and either gave up or fell back to shell
guessing. Two compounding causes:
1. The system prompt block injected by SkillRuntimeService listed each
skill as `- **RedisOps** — desc`, which is the same format used for
tool catalogs and primed the model to call the names directly. The
"how to use" instructions referenced `read_skill_file` /
`run_skill_script` — names that don't exist in the tool registry,
so even a compliant LLM couldn't follow them.
2. ToolExecutionExecutor's `callback == null` branches returned a bare
"Tool not found: <name>" string. The model had no recovery signal
and no hint that the name it called was actually a skill.
Fix is two-layered:
- Prompt rewrite (SkillRuntimeService.buildSkillPromptEnhancement): lead
with an explicit warning that skills are NOT directly callable, use the
correct camelCase tool names (readSkillFile / runSkillScript), include
a concrete worked example anchored to the first enabled skill, and
render the listing as a markdown table so it stops looking like a
callable tool list. listAvailableSkills tool description and output
follow the same pattern.
- Runtime safety net (ToolExecutionExecutor): when toolCallbackMap.get
misses, check if the requested name (case-insensitive) matches an
active skill. If so, return a precise hint telling the LLM the right
invocation pattern instead of the bare error. Wired through both the
main execute path and the pre-approved replay path. SkillRuntimeService
is attached via a setter from AgentGraphBuilder so the executor's many
legacy constructors stay untouched, and it's nullable so isolated
tests still work.
Adds 5 unit tests covering: skill match -> hint, case-insensitive match,
no-match -> bare error, no SkillRuntimeService wired -> bare error,
pre-approved replay path -> hint.
Reported and reproduced by @pipima9950-glitch in issue #46.
SkillPackageResolver.persistScanOutcome built a fresh SkillEntity with only
id + scan fields, then called updateById. SkillEntity declares six columns
with @TableField(updateStrategy = FieldStrategy.ALWAYS) — name_zh, name_en,
config_json, source_code, skill_content, security_scan_result — so the
ALWAYS strategy emits UPDATE statements that write NULL to every one of
those columns not set on the partial entity.
Effect: every security re-scan that produced a status/findings change
silently wiped skill_content, config_json, source_code, name_zh, name_en
on the row. After importing a custom skill, the first scan tick destroyed
the imported content.
Fix: switch to LambdaUpdateWrapper so the UPDATE only touches the three
scan columns we actually want to change. Other skillMapper.updateById
call sites (SkillService, BuiltinSkillSeedService) pass DB-hydrated
existing entities and are unaffected.
Reported and diagnosed by @pipima9950-glitch in issue #45.
Three layers landed together because they share the same routing /
lifecycle plumbing:
1. Cron output unification
- New CronConversationResolver routes web-origin jobs to the per-workspace
tasks_<wsId> conversation; IM-bound jobs go to the channel session
conversation when one exists (matched by senderId then targetId);
legacy cron_<id> remains as the fallback.
- CronJobLifecycleService inserts a system-role header divider when a
run starts so users browsing the unified tasks_<wsId> view can tell
which job started a run. BaseAgent.sanitizeForLlm filters these
headers so they never reach the model.
- WorkspaceService seeds tasks_<wsId> on workspace creation; V65
migration backfills existing workspaces.
- DeliveryConfig gains a userId field so IM session lookup can match
by senderId (replyToken-based targetId is not stable across runs).
- ConversationVO recognizes tasks_/cron_ underscore prefix as cron
source. MessageList renders the system header as a labeled divider.
- ChatConsole pins tasks_* conversations and tracks per-conversation
read state so new cron output gets a visible unread dot.
2. Reminder task type
- New task_type='reminder' in CronJobEntity + service validation.
- CronJobRunner short-circuits 'reminder' jobs: hands trigger_message
to finishRunAndPublish verbatim, no LLM call. Fixes a regression
where reminders were rephrased into echoed wrappers.
- New create_reminder tool alongside create_cron_job, with descriptions
tightened so the model picks the right one (verbatim push vs LLM
query that needs computation).
- CronJobs.vue gets a third radio option + dedicated reminder field.
3. In-flight progress placeholder
- Cron uses non-streaming chat()/execute(); tool-heavy ReAct loops
can run 1-5 minutes between start and finish with no visible
state, looking hung.
- New GET /api/v1/cron-jobs/active-runs returns runs in status=running
for a conversation. ChatConsole polls it on the existing 4s tick
(and on conversation switch) and shows a spinner bar with elapsed
time. When run count drops to zero, it refetches messages so the
assistant bubble appears within ~1s of finish.
Add a callout above the existing intro to make the wedge explicit:
multi-user workspaces, approval-gated sensitive actions, full audit trail,
production-grade health monitoring, per-channel error isolation.
One JAR on your own machine, zero data egress.
Chat attachments with non-ASCII filenames (e.g. Chinese) get sanitized
at upload time — `人人有虾.docx` is stored as `1777391026594_____.docx`.
Tools then receive only the original filename via '[Attachment] foo.docx'
and fail with 'file not found'.
- renderMessageContent now appends the actual server-side path so any
tool the LLM picks (read_file / extract_document_text /
detect_file_type) gets a path that resolves directly.
- New ChatUploadResolver helper performs basename-suffix matching inside
the conversation's chat-upload directory; ReadFileTool, DocumentExtractTool
and FileTypeDetectorTool fall through to it when the literal path does
not exist (defense in depth for cases where the LLM ignores the path
hint).
Refs https://github.com/matevip/mateclaw/issues/29
Replace the per-startup admin reconciliation in
WorkspaceSchemaMigration.ensureDefaultWorkspaceMembership() with a
one-shot bootstrap. Once the default workspace has any owner, the
method returns immediately, so an operator's deliberate removal of an
admin from the default workspace persists across restarts. If no owner
exists yet, pick the lowest-id active admin and add them as owner; if
no admin exists at all, log a warning and skip rather than failing
startup.
Refs https://github.com/matevip/mateclaw/issues/29
Restart-time backfill in WorkspaceSchemaMigration was inserting every
existing user into the default workspace and copying mate_user.role
('user'/'admin') into mate_workspace_member.role, whose valid domain is
{owner, admin, member, viewer}. Result: non-admin users assigned to
other workspaces were silently re-attached to the default workspace
with role='user', failing roleLevel() lookup and 403'ing on Agents.
- Filter the INSERT on u.role = 'admin' and hard-code the membership
role to 'owner', removing the role-domain mismatch and the
workspace-isolation violation in one change.
- Add V60__fix_invalid_workspace_member_roles.sql (h2 + mysql) to
drop already-corrupted default-workspace rows for users who have a
valid membership elsewhere, and downgrade the orphan rows to
'member' so those users aren't locked out entirely.
Refs https://github.com/matevip/mateclaw/issues/29
