* fix(agent): stop executing illustrative Markdown fences as tool calls for native function-calling models
_resolve_tool_blocks fell back to the textual parse_tool_blocks() fenced-block
parser whenever a model produced no native tool_calls, regardless of whether
that model has a reliable native function-calling channel. Native models
(GPT/Claude/Grok/Qwen3/DeepSeek-V, etc. - _is_api_model true) commonly write
illustrative ```bash/```python/```json examples in guide-only prose; the
fallback parser matched these and executed them as real commands, sometimes
looping for several rounds as the model tried to clarify with more examples
(#3222).
Restrict the textual fenced-block fallback to non-native models, which rely
on it as their only tool-invocation channel. Native models are trusted to use
their structured tool_calls channel for real invocations; when they don't
emit one, a bare fence in their response is prose, not an action. The native
tool_calls path itself is untouched.
This sits one layer below #3088's guide-only policy enforcement: that PR
blocks tool exposure/execution on explicit no-tools requests, while this fixes
the parser so ordinary illustrative fences are never misread as calls in the
first place, on any turn.
* fix(agent): gate only the fenced-example pattern for native models, preserve DSML/invoke recovery and persistence
_resolve_tool_blocks previously short-circuited the entire textual parser
(tool_blocks = [] if is_api_model else parse_tool_blocks(...)) for native
function-calling models with no native tool_calls. That also dropped Patterns
2-5 (explicit [TOOL_CALL]/<invoke>/<tool_code>/DSML markup leaked into content
as text), which are real calls a model couldn't emit on its structured channel
(e.g. DeepSeek-V falling back to DSML), not illustrative examples.
parse_tool_blocks/strip_tool_blocks now take a skip_fenced flag that gates ONLY
Pattern 1 (the fenced ```bash/```python/```json block matcher). _resolve_tool_blocks
passes skip_fenced=is_api_model so fenced examples stop being executed for
native models while [TOOL_CALL]/<invoke>/<tool_code>/DSML stay fully active and
recoverable. cleaned_round mirrors the same gate when persisting round text, so
an illustrative fence that wasn't executed isn't stripped from saved/reloaded
history either (it was streaming once and then disappearing on reload).
Models (notably Gemini) emit a native 'google_search' function call, but the
agent loop had no mapping for it, so the call failed to convert, the round
produced 0 chars and 0 tool blocks, and generation died silently — the web
client hung on 'waiting for first token' with no error (also #443).
- Map google_search / google_search_retrieval / google_search_grounding to the
web_search tool, and read Gemini's 'queries' array (falling back to 'query').
- In stream_agent_loop, when a round yields no response text and no tool
events, emit a visible fallback message instead of leaving the user hanging.
- Give the unknown-tool execution branch an explicit exit_code=1 so the failure
is logged as an error rather than 'n/a'.
Unknown/unconvertible tool names still return None (unchanged) so they are
dropped safely rather than executed. Added tests covering the google_search
mapping, the queries array, and unknown/invalid-JSON returning None.
* feat(web-fetch): add web_fetch tool to read a specific URL's content
* test(web-fetch): add SSRF coverage and fail closed on empty DNS resolution
Add explicit SSRF regression tests for the web_fetch path covering
loopback, private LAN ranges, link-local/metadata, IPv6 private/local,
redirect-into-private, and unsupported schemes. Harden _public_http_url
to fail closed when a hostname resolves to no addresses.
Lucas Daniel