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.
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.
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
User-reported field issues + a deeper code audit revealed multiple
overlapping bugs in the prior cron-channel delivery change. This fixes
all six.
#1 — Concurrency race on ToolExecutionExecutor (root cause of 'sometimes
succeeds, sometimes fails' tool calls). The volatile instance fields
currentRequesterId / currentWorkspaceBasePath / currentChatOrigin
were shared by every conversation routed through the same per-agent
executor; one user mid-build-loop while another's execute()
overwrote the field would cross-contaminate the captured values into
PreparedToolCall. Fix: kill the instance fields, thread
origin/requester/workspace as method params straight into
PreparedToolCall snapshot. Comment pins the rule so it cannot regress.
#2 — CHAT_ORIGIN missing from KeyStrategyFactory (latent timebomb,
masked by spring-ai-alibaba-graph-core's non-filtering builder path).
Without an addStrategy registration, multi-node state merges in long
ReAct / Plan-Execute loops drop the key, ActionNode reads
ChatOrigin.EMPTY, and the cron persists with channel_id=NULL. Also
caught 4 more keys that were latently unregistered:
WORKSPACE_BASE_PATH, STOP_REQUESTED, RETURN_DIRECT_TRIGGERED,
DIRECT_TOOL_OUTPUTS. All five now registered in both ReAct and
Plan-Execute factories.
#3 — CronJobs UI didn't surface channel binding. CronJobDTO carried
channelId / deliveryConfig but the list page never rendered them.
Added: (a) 'channel' column on list page, (b) channel + targetId
rows in the detail modal, (c) backend batch-loads channel names via
ChannelMapper.selectBatchIds so the column shows the human-readable
name, (d) i18n keys (zh + en), (e) channelName field on TS CronJob
type.
#4a — DingTalk targetId expiry. ChannelChatOriginFactory.resolveTargetId
used to prefer ChannelMessage.replyToken which for DingTalk encodes
a sessionWebhook URL that expires ~90 minutes after the inbound
message. Cron persisted with that webhook then dies with 401/403 and
marks NOT_DELIVERED forever. Fix: prefer the stable chatId, fall
back to senderId — both work indefinitely via DingTalk's Robot API.
#4b — Scheduler pool exhaustion under long LLM. CronJobService's
ThreadPoolTaskScheduler ran with poolSize=4 AND the LLM call lived
on the scheduler thread. Four concurrent crons saturated the pool
and the 5th silently missed its tick. Fix: keep scheduler tiny (it
just fires triggers) and offload runAgent to a dedicated
virtual-thread executor (cron-execute-* threads). LLM workload is
I/O-bound — virtual threads scale to thousands at trivial cost.
#5 — Minor latent bugs:
- AbstractCronResultDelivery.claimRun used .in(... 'NONE','PENDING',null),
but SQL IN never matches NULL. Rewrote as IS NULL OR IN
(NONE,PENDING) so legacy pre-V57 rows can still claim.
- CronDeliveryListener.onCompletedRaw was an empty @EventListener
with a wrong-headed comment about test fallbackExecution. Removed.
- CronJobTool.resolveAgentId silently returned 1L when origin
lacked an agentId — would silently bind to whatever agent #1
happens to be. Replaced with explicit error so wiring bugs surface
immediately instead of producing scheduled-but-never-runs crons.
State-key registration guard. New StateKeyRegistrationCoverageTest
scans MateClawStateKeys via reflection and parses
AgentGraphBuilder.java to extract every
.addStrategy(MateClawStateKeys.X, ...). Asserts every non-_NODE
constant appears in at least one factory. Caught the 4 unregistered
keys above on first run; will catch any future 'forgot to register'
regression.
Tests: 33 unit/arch tests + 27 regression in touched areas — all green.
Vue typecheck clean.
Refs: #25, #16
Replaces the prior ThreadLocal context plumbing with explicit Spring AI
ToolContext threading carried by an immutable ChatOrigin value object,
so a cron created from inside WeChat (or any IM channel) delivers its
results back to the originating channel.
Architecture
- ChatOrigin / ChannelTarget value objects + per-entry-point factories
(ChannelChatOriginFactory in vip.mate.channel, CronChatOriginFactory
in vip.mate.cron — symmetric, no cyclic deps).
- LocaleAwareToolCallback now forwards call(String, ToolContext) and
getToolMetadata so the decorator chain cannot silently drop the origin.
- AgentService 6-method overhaul + ChatOriginHolder bridge into
StateGraph buildInitialState which writes CHAT_ORIGIN; ActionNode +
StepExecutionNode forward it to ToolExecutionExecutor.
- ToolExecutionExecutor builds ToolContext per call; 8/8 tools migrated
(CronJobTool, WorkspacePathGuard, Video/Image/Browser/ReadFile/Music,
DelegateAgentTool with parent-origin inheritance).
- CronJobRunner + CronJobLifecycleService 3-segment REQUIRES_NEW model
(T1 startRun / no-tx runAgent / T2 finishRunAndPublish); ArchUnit
pins CronJobRunner as @Transactional-free.
- CronResultDelivery Strategy + AbstractCronResultDelivery Template
with SQL CAS idempotency on mate_cron_job_run.delivery_status —
replaces the prior process-local Caffeine TTL, cluster-safe.
- CronJobCompletedEvent + @Async @TransactionalEventListener(AFTER_COMMIT);
cronDeliveryExecutor (core=2, max=4, queue=1000, AbortPolicy + audit).
- CronRunStaleCleanup @Scheduled(5min) sweeps PENDING-15min and
status='running'-30min in one query each.
- CronJobRunner.wrapWithDeliveryGuard prepends a system note for
channel-bound crons to suppress hallucinated 'install CLI to send
WeChat' suggestions.
- ApprovalWorkflowService Memento: persist ChatOrigin snapshot on
create, restore on replay so cross-restart approvals keep channel
binding; ChannelMessageRouter + ChatController web-replay both prefer
the Memento and fall back to fresh-build.
- ChannelManager.sendToChannel 4-arg DeliveryOptions overload;
ChannelAdapter#proactiveSend default 4-arg pass-through; Slack
overrides for thread_ts and Telegram overrides for message_thread_id.
- CronJobs UI: read-only 'last delivery' badge driven by
CronJobMapper.selectListWithDeliveryStatus subquery.
Schema migrations V57/V58/V59 (V56 was already taken by an unrelated
provider migration — Flyway processes versions in order regardless of
gaps):
- V57: mate_cron_job_run delivery_status / target / error + composite
index (delivery_status, started_at) covering the cleanup sweep.
- V58: mate_cron_job channel_id (indexed) + delivery_config TEXT (JSON
via MyBatis Plus JacksonTypeHandler).
- V59: mate_tool_approval chat_origin TEXT (Memento).
All idempotent in both H2 (IF NOT EXISTS) and MySQL (INFORMATION_SCHEMA
guard + PREPARE).
ArchUnit guards (test scope, archunit-junit5 1.3.0):
- every concrete vip.mate.* ToolCallback must override
call(String, ToolContext) — pins the decorator-forward fix.
- CronJobRunner must NOT carry @Transactional on the class or any
method — pins the 3-segment lifecycle rule.
Tests: 32 new unit tests + 21 regression tests in touched areas, all
53 green:
- ChatOriginTest (6) — value-object invariants + JSON round-trip.
- LocaleAwareToolCallbackToolContextTest (2) — decorator forward.
- DeliveryConfigTest (4) — Jackson round-trip + forward-compat.
- ToolCallbackToolContextForwardArchTest (2) — both ArchUnit guards.
- CronJobRunnerDeliveryGuardTest (3) — channel-cron prefix injection.
- AbstractCronResultDeliveryTest (4) — claim CAS + concurrent CAS.
- ChannelCronResultDeliveryTest (6) — supports / doDeliver / errors.
- ApprovalReplayContinuityTest (5) — Memento round-trip + corrupt
payload fallback + unknown-field tolerance.
Refs: #25, #16
Issue #24: tools selected in the agent binding UI had no effect at runtime.
mate_tool.name stores the Java class name (e.g. "BrowserUseTool") and was
written into mate_agent_tool.tool_name, but AgentToolSet.withAllowedToolsOnly
matched by the @Tool function name (e.g. "browser_use") — so every binding
was silently filtered out.
Fix: AgentToolSet builds an alias index per ToolCallback indexed by every
equivalent identifier — function name, Spring bean name, and Java class
simple name. withAllowedToolsOnly / withDeniedToolsFiltered / excluding
all accept any of these aliases, mirroring how Spring's BeanFactory accepts
bean names + aliases.
ToolRegistry.getEnabledToolSet now threads a bean→beanName resolver into
the new AgentToolSet.fromCallbacks(...) overload. Existing two-arg callers
keep working; tests pass without changes.
Zero data migration: stale mate_agent_tool rows that previously had no
effect now resolve correctly via the class-name alias.
The two tools-sync scripts ran on every startup and used H2 MERGE INTO
... KEY(id), which overwrites every column on existing rows. That
silently reverted UI-toggled `enabled` and was the proximate cause of
a recent WriteFileTool/EditFileTool outage.
They were also a strict subset of the fresh-install seed (data-zh.sql /
data-en.sql register all 19 builtins; the sync scripts only 16) and out
of date. Per-tool Flyway migrations (V3, V31) are already the canonical
'register a new builtin' path, so the sync layer was duplicated and
error-prone.
Delete both files and the runToolSyncScript() loader. Tool descriptions
shown to the LLM come from @Tool annotations in code, not the DB row,
so removing per-startup metadata refresh has no functional impact.
Two follow-up improvements on top of renderDocxFromFile so the docx
pipeline can handle real long-form deliverables instead of just
prose-only memos.
Image embedding (P1).
MarkdownDocxRenderer now recognizes single-line  markdown
and embeds the referenced file via POI's XWPFRun.addPicture():
- PNG / JPG / GIF / BMP read straight from disk
- SVG rasterized via Apache Batik (PNGTranscoder, target width 1400px)
before embedding — OOXML stores raster images, so any vector source
needs conversion. Batik runs in-JVM, no rsvg-convert / cairo on host.
- Pictures are pinned to roughly the printable page width (≈ 5.77 in
for A4 minus default 1800-twip margins) and given a 4:3 height
fallback. Mixing images inline with other paragraph text is not
supported by design — the markdown subset assumes one image per
block paragraph. Inline images would require splitting paragraphs
across runs with explicit positioning, well beyond what this
renderer covers.
- Failure modes (missing file, unsupported format, Batik blowing up)
emit an italicised "[image: alt — reason]" placeholder so the rest
of the document still renders; the agent can read its own log to
see why the picture didn't make it.
- Adds two transitive deps via pom: batik-transcoder + batik-codec at
1.18, ~10 MB combined. Worth it given the alternative is shelling
out to system tooling.
Multi-file render (P2-lite).
New tool renderDocxFromFiles(List<String> filePaths, filename, pageSize)
reads several markdown files in order and renders one combined docx.
Lets the agent split a 30-page proposal into cover.md / ch1.md /
ch2.md / appendix.md and produce a single deliverable in one tool
call. Each path goes through WorkspacePathGuard.validatePath; any
empty or unreadable file aborts with a typed error so the agent
fixes its file list before retrying. Files are joined with a blank
line — no separator markup is injected, headings carry over cleanly.
I deliberately did NOT build the heavier mutable-docx state
("appendDocxChapter / finalizeDocx") flavor of P2: the multi-file
form covers the same workflow with no per-conversation state to
clean up, and the agent can iterate by rewriting the chapter file
and re-running the tool. Stateful append can come later if a
streaming use case actually shows up.
renderDocx and renderDocxFromFile @Tool descriptions updated to point
the agent at renderDocxFromFile for >5 KB markdown and to advertise
the new image-embedding capability.
renderDocx requires the markdown body to flow through the LLM as a
tool argument. For an 80 KB project proposal that's ≈ 20 K tokens of
streaming output spent just to repeat back content the model already
wrote to disk a turn earlier — multi-minute generation, real money.
renderDocxFromFile takes a file path instead. The agent uses
write_file / edit_file to assemble the markdown locally, then calls
this tool with just the path. JVM reads the file in one IO syscall
and feeds it to the existing MarkdownDocxRenderer. Token cost drops
from ≈ 20 K to ≈ 50 (the path string).
Behavior:
- Path resolution honors WorkspacePathGuard, same boundary as
read_file / write_file. No path traversal.
- UTF-8 read; rejects empty / missing / non-regular paths with
typed error messages so the agent can recover.
- Output cached in GeneratedFileCache and returned as a relative
/api/v1/files/generated/{id} link, with the same anti-host-
hallucination instruction renderDocx already carries.
- Same supported markdown subset (headings, bold, lists, tables).
Image references () still render as raw text — full
image embedding (P1) and SVG → PNG conversion (also P1) need
Apache Batik plus image-rendering plumbing in MarkdownDocxRenderer
and is tracked separately. Chapter-mode merge (P2) likewise needs
its own plumbing.
The @Tool description tells the agent to prefer this path when
markdown exceeds ~5 KB and shows the full write_file →
renderDocxFromFile workflow inline.
Three small but high-impact fixes that all surfaced together while
verifying the long-form generation flow.
1. ChatConsole onBeforeUnmount no longer kills the backend turn.
Previously, switching tabs / route navigation / any cause that
unmounted the chat view called stopChatGeneration(), which POSTs
/chat/{cid}/stop and aborts the in-flight LLM call. The user
reported a turn dying mid-generation just from switching pages.
Replaced with resetForNewConversation() — front-end SSE disconnect
only, no /stop. Backend keeps running; pollActivity / status probe
reconnects on return. Aligns with the existing comment in
selectConversation: "let A's backend agent run continue running."
2. Agent max_iterations raised 25 → 100 with a hard ceiling.
The previous 25-step ceiling caused LimitExceededNode to fire on
substantive multi-tool tasks (document generation + image conversion
+ retry loops). 100 matches QwenPaw's _MAX_MAX_ITERATIONS upper
bound. New plumbing:
- BaseAgent.MAX_ITERATIONS_HARD_CEILING = 100 public constant
- BaseAgent default field 25 → 100 (Java-side fallback)
- AgentGraphBuilder clamps any per-agent DB override to the
ceiling at runtime; if the row holds 200, runtime sees 100 and
a WARN is logged with the original value.
- V47 migration (h2 + mysql) idempotently bumps the three default
seeded agents (1000000001, 1000000002, 1000000003) only if they
still hold the old defaults (25 / 20). User-customized values
are not touched.
- data-en/zh/-mysql-en/-mysql-zh seed files updated to 100 for
fresh installs.
3. DocxRenderTool tells the LLM not to prepend a host to the URL.
DeepSeek and Claude have both been observed wrapping the
/api/v1/files/generated/{id} relative path returned by renderDocx
into an absolute URL with a hallucinated domain (e.g.
https://ai-tools-system.com/...), breaking the download link in
the rendered chat bubble. The tool's return string now appends an
explicit "must use the relative path verbatim, do not add any
https:// or http:// prefix" instruction, which Claude and
DeepSeek both honor.
