fix(gooddata-eval): persist skill_routing credit across conversation turns - #1762
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Included review availability: Your plan provides up to 1 included review per hour; 0 remain after this review. 📝 WalkthroughWalkthroughConversation evaluation now separates the active skill set from cumulative skill declarations. Skill replacement, clearing, inheritance, routing, result details, trace links, scoring, and assertion handling use the updated semantics. ChangesConversation skill state and evaluation
Estimated code review effort: 3 (Moderate) | ~25 minutes Merge Risk: ⚪ Minimal · up to Conversation skill routing now preserves active skills across turns while correctly handling replacement, clearing, and cumulative coverage. The covered behavior has no identified merge-blocking risk. Suggested reviewers: Poem
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The bug is real and the debug provenance in the test docstring (t4/t5 of Is
activated_skills_so_far |= set(activated)
skill_routing = turn.expected_skill in activated_skills_so_farThat's correct if the platform treats
If replace semantics apply, the state to track is "last set wins, carried over when a turn issues no call of its own": if activated:
active_skills = set(activated)
skill_routing = turn.expected_skill in active_skillsThe two implementations disagree on real multi-skill fixtures, so it's worth confirming with the platform side rather than inferring. If additive is confirmed, the current code is right as-is and it'd be good to say so in the comment — that's the assumption the whole fix rests on. Reporting now self-contradicts.
{"turn_id": "t5", "skill_routing": true, "activated_skills": []}which reads as a bug to anyone triaging a report — the credited skill is nowhere in the list the same record shows. Either report the set the credit was drawn from, or add a field distinguishing "activated this turn" from "active during this turn". (This is also the payload #1757 serializes, so the two PRs meet here.)
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@hkad98 good catch, and I don't want to guess on this one. The additive-vs-replacing question determines whether the current fix is correct or just moves the bug — I can't verify Once that's settled: if additive is confirmed, I'll add a comment here stating that assumption explicitly (agreed, the code should say why it's safe, not just that it works). If it's replacing, I'll switch to the "last set wins, carried over when a turn issues no call" version you sketched. The reporting self-contradiction ( |
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Agreed — holding is the right call here, and I'd rather have this open pending an answer than merged on a guess. Nothing further from me on the accumulation logic until the semantics land. Two things to make the answer easier to get, since whoever knows 1. The actual question to ask. Concretely: after 2. A related inconsistency to confirm at the same time — the argument key. skills.extend(args.get("skill_names") or args.get("skills") or [])but the visualization evaluator only reads one: # evaluators/visualization.py:78
skill_names = args.get("skill_names", [])Our own tests use both — Also fine to fix the |
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@hkad98 addressed the reporting half in The two fields measure different scopes on purpose, and that wasn't written down anywhere — which is why the output reads as a bug:
So I deliberately did not change what Still need that answer before touching the accumulation logic or the field's contents — that's the one thing here I can't settle from the repo. 475 passed, lint clean. |
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@hkad98 checked the gen-ai service implementation — it replaces, it does not accumulate. Your suspicion was right and the original fix here was wrong. So the running union produced exactly the false PASS you described. Concretely, with the old code: t1 Fixed in if activated:
active_skills = set(activated)
skill_routing = turn.expected_skill in active_skillsThe original false-FAIL fix still holds — a turn reusing an already-active skill without re-declaring keeps its credit; only turns whose skill was actively replaced lose it. Also took the second option you offered on reporting: added New test One thing I noticed while checking, not fixed: (Ping me directly if you want the specific implementation references I checked — keeping them out of this repo's comments.) |
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@hkad98 sorry — I'd already gone and answered the semantics question before reading this, so my earlier comments crossed yours. Both your points are settled now: 1. Semantics — it replaces. Checked the gen-ai service directly (not inferred): the registry's setter assigns the resolved set outright rather than merging, and the tool's own parameter/description text says it replaces and does not append. Your third possibility (per-request re-derivation) is ruled out — the active set is instance state on the registry that persists across turns until the next 2. The argument key — The bug was on our side, in the tests: I left the Ready for review whenever — no open questions from my side now. |
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In `@packages/gooddata-eval/src/gooddata_eval/core/agentic/conversation.py`:
- Around line 405-406: Update the skill activation handling around active_skills
and set_skills so declarations use replacement semantics: track whether
set_skills was called independently of its payload, retain only the final
declaration, and replace prior skills even when the final list is empty. Add
regression coverage for multiple declarations and explicit clearing, ensuring
stale skills cannot produce false skill_routing.
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packages/gooddata-eval/src/gooddata_eval/core/agentic/conversation.pypackages/gooddata-eval/tests/test_agentic_conversation.py
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Thanks for going and checking the service — replace semantics confirmed, and the skill_names correction is good news I'd got backwards, so thanks for stating it plainly rather than just fixing it. _final_skill_declaration is the right primitive, and keeping None distinguishable from [] is a detail that would have been easy to miss. d3a902fb (last declaration wins within a turn) is the subtle one and it's correct.
But narrowing activated_skills broke full_skill_coverage, and it's a false FAIL of exactly the kind this PR set out to remove.
activated_skills went from "union of every set_skills call in the turn" to "only the final declaration". full_skill_coverage still unions that field across turns and is untouched by this PR:
# conversation.py:461 — unchanged
activated_all = {skill for tr in turn_results for skill in tr.activated_skills}
full_skill_coverage = set(fixture.expected_skills).issubset(activated_all)So a skill a turn declared and then replaced within that same turn now vanishes from coverage, even though it genuinely was activated. I ran the same scenario against both trees:
master |
this branch | |
|---|---|---|
activated_skills |
['visualization', 'metric'] |
['visualization'] |
full_skill_coverage |
True | False |
The scenario is one logical turn with a clarification round — the exact case _final_skill_declaration's own docstring describes ("these events span every clarification sub-turn within one logical turn"): sub-turn 1 declares metric and produces no output, sub-turn 2 declares visualization and completes. expected_skills = ["metric", "visualization"], both genuinely activated, coverage now says otherwise. Repro:
mock_client.send_message.side_effect = [
ChatResult.model_validate({"textResponse": "which one?", "toolCallEvents": [_skills_tc("metric")]}),
ChatResult.model_validate({"textResponse": "done", "toolCallEvents": [_skills_tc("visualization"), _create_metric_tc("m1")]}),
]
fixture = ConversationFixture(
id="probe", expected_skills=["metric", "visualization"],
turns=[TurnDefinition(turn_id="t1", message="go", expected_skill="visualization", expected_output_type="metric")],
)
# -> result.full_skill_coverage is False on this branch, True on masterNote this only bites within a turn. Across turns it's fine — t1 declaring metric and t2 declaring visualization still gives each turn its own activated_skills and the union still sees both. That's probably why the suite stays green at 478.
The two fields answer different questions and now need different data:
skill_routing/active_skills— "was it active at this point". Replace semantics, last-wins. Correct as implemented.full_skill_coverage— "did the conversation ever exercise every expected skill". That's inherently cumulative over all declarations, and replace semantics don't change it: a skill that was on and later switched off was still exercised.
So it needs its own accumulator rather than being derived from activated_skills. Something like having the parser hand back every declaration it saw, or tracking ever_declared: set[str] alongside active_skills in the loop and using that at line 461. Worth a test in the shape of the repro above, since the existing coverage tests all declare once per turn and can't see this.
Two much smaller things while you're in here:
activated_skills=declared or []collapses theNone/[]distinction that_final_skill_declarationworks to preserve — an explicitset_skills([])and no call at all both report[].active_skillsdisambiguates them in practice (unless the carried set was already empty), so this is cosmetic, but it's a shame to build the distinction and then drop it at the boundary.- The
_resolve_refsskip path appends aTurnResultwithoutactive_skills, so it defaults to[]even when a set is currently carried over. Harmless on a skipped turn, mildly misleading in the report.
The _activated_skills-should-read-the-result observation is a good catch and I agree it's separable — the tool echoing back the authoritative post-replacement set is strictly better than re-deriving from arguments, especially given the dependency-pulling you mention. Worth its own issue; happy to see it filed. Same for dropping the now-provably-dead or args.get("skills") fallback.
…turns _activated_skills() only looked at the current turn's tool calls, so skill_routing was recomputed from scratch each turn. The platform keeps a skill active once set_skills is called, so an agent correctly omits a redundant set_skills call on a later turn that reuses the same skill -- but the scorer forced skill_routing=False whenever no skill was activated *this* turn, regardless of whether it was already active. Found via scripts/authoring/debug_conversation.py replaying analyst-explores-dynamic-currency-conversion (gdc-mic-ai-evaluation repo): turns t4/t5 both ran create_adhoc_visualization/create_metric successfully against an already-active skill, yet scored FAIL solely on this. Track activated skills in a running set across the whole conversation instead of resetting it every turn.
… differ in scope Addresses the reporting half of hkad98's review: with skill_routing now cumulative while TurnResult.activated_skills stays per-turn, a reused-skill turn reports skill_routing=True alongside activated_skills=[], which reads as a scoring bug to anyone triaging a report. The two fields measure different scopes on purpose -- activated_skills is "what THIS turn declared", skill_routing is "was expected_skill active by this point in the conversation". Documented on TurnResult and at the computation site, and pinned by an assertion on the existing persistence test so the combination is recorded as intended output. Deliberately not changing what activated_skills CONTAINS: whether the cumulative set is the right value to report depends on whether set_skills is additive or replacing, which is still open. This makes today's output legible under either answer without pre-committing to one.
set_skills REPLACES the active skill set rather than adding to it -- verified against the gen-ai service's skill registry, and stated in the tool's own description. The running union this PR originally used was therefore wrong in the mirror case hkad98 predicted: a skill dropped by a later set_skills call stayed credited, so a turn expecting it and declaring nothing scored PASS against a skill that was no longer active. That is strictly worse than the false FAIL this PR set out to fix -- it reports a broken conversation as working. Now tracks "last declared set wins, carried over on turns that declare nothing", which matches the platform. The original false-FAIL fix still holds: a turn reusing an already-active skill without re-declaring it keeps its credit. Also reports the set the credit was drawn from as TurnResult.active_skills (and in detail["turns"]), so skill_routing=True next to activated_skills=[] is self-explanatory instead of reading as a scoring bug. New test asserts the deactivation case and fails under the old union logic (verified by re-injecting it).
…tion tests
_skills_tc emitted {"skills": [...]}, but the set_skills tool declares and
reads `skill_names`. The conversation tests therefore only passed via
_activated_skills' fallback spelling, exercising a payload shape the platform
never sends -- including the new deactivation test.
Switched to `skill_names`; all 23 tests still pass, which now demonstrates the
real path rather than the fallback.
The fallback in _activated_skills is left in place (harmless, and removing it
is a separate behaviour change).
Two holes in the replace-semantics fix, both found by CodeRabbit: 1. _activated_skills merged the names from every set_skills call in the turn's tool-call list -- which spans all its clarification sub-turns -- so a turn calling set_skills(["metric"]) and later set_skills(["visualization"]) was credited for both. That is the same union bug one level down: the second call replaced the first, so only visualization is active. 2. An explicit set_skills([]) was indistinguishable from making no call at all, because the guard tested the list's truthiness. An empty declaration deactivates everything; no call carries the previous set over. Conflating them left the turn credited for the previous turn's skills. Replaced with _final_skill_declaration(), returning the last call's list or None when there was no call, so "cleared" and "not declared" stay distinct. Both cases now have regression tests, each verified to fail against the merge- and-truthiness version before being kept.
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Rebased onto master ( The collision was with #1757, now merged: it replaced the hand-written 706 passed, lint and format clean. Two notes:
No open questions from my side. |
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The rebase is right — I checked it, and resolving in favour of #1757's shape (drop the literal, add But "no open questions from my side" crossed my review — I left a changes-requested at 08:01, ten minutes before your comment, and I don't think you'd seen it. There's one open item and it isn't the rebase:
That commit is correct for what it set out to do — CodeRabbit's merged-declarations finding was real and last-declaration-wins is the right fix for # conversation.py:491 -- unchanged by this PR
activated_all = {skill for tr in turn_results for skill in tr.activated_skills}
full_skill_coverage = set(fixture.expected_skills).issubset(activated_all)
One logical turn with a clarification round — sub-turn 1 declares The two metrics need different data:
So it needs its own accumulator — Worth confirming the intent before you write it, though: I've assumed Happy to push the accumulator version myself if you'd rather not respin — say the word. Otherwise this is the only thing between here and an approval; everything else on this PR is in good shape. |
full_skill_coverage was derived from TurnResult.activated_skills, which d3a902f narrowed from "every set_skills declaration in the turn" to "only the final one". A skill a turn declared and then replaced across its own clarification sub-turns therefore vanished from coverage despite having been genuinely activated -- a false FAIL of the kind this PR set out to remove. The two metrics ask different questions and now use different data: - skill_routing / active_skills -- "is it active at this point". Replace semantics, last declaration wins. Unchanged. - full_skill_coverage -- "did the conversation ever exercise this skill". Cumulative over all declarations; a skill switched on and later off was still exercised, so replace semantics do not apply. Adds _set_skills_declarations() returning every declaration in call order, with _final_skill_declaration() now taking the last of those, and an ever_declared_skills accumulator feeding coverage. Also reports the carried-over active set on the $ref-skip path, which previously defaulted to [] and read as "nothing was active". Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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You're right, and my "no open questions" was written without having seen your review — apologies, that's the second time I've crossed you on this PR. Reproduced your scenario against On the intent question: yes, "declared at some point" is what it means. Fixed in declarations = _set_skills_declarations(all_tool_calls)
for declaration in declarations:
ever_declared_skills.update(declaration)
declared = declarations[-1] if declarations else NoneI split out Coverage now uses Test added in the shape of your repro ( On your two smaller points:
707 passed, lint and format clean. Also worth flagging, since it's fallout from renaming Filing the two separable items you agreed on (reading the tool result rather than its arguments; dropping the dead |
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Verified and approving. Thanks for confirming the intent question rather than just patching to make my repro pass — "coverage is a question about the fixture, correctness is skill_routing/conversation_success" is the right framing and it's the reason the accumulator is correct rather than merely different.
What I checked on 3e1d84d3:
| Check | Result |
|---|---|
| My original repro | full_skill_coverage = True (was False), skill_routing still True, activated_skills == ['visualization'] |
| Full suite | 707 passed — matches your number |
| New tests actually catch the regression | Re-injected the activated_skills-derived coverage; ..._coverage_counts_a_skill_replaced_within_its_own_turn and ..._only_the_last_set_skills_call_in_a_turn_counts both fail, 2 failed / 26 passed |
| Skip path | active_skills=sorted(active_skills) at both construction sites |
Splitting _set_skills_declarations() out and having the two questions read one parse is better than what I suggested — I'd have had you accumulate in the loop and left the parser answering only the "what's active now" question, which is the coupling that caused this in the first place. Naming the trap in a comment at ever_declared_skills is the right call too; that's exactly where the next person would reach for activated_skills.
One leftover: _final_skill_declaration() is now dead. The loop inlines declarations[-1] if declarations else None (correctly — calling the helper would parse twice), so nothing in src or tests references it. Worth deleting and folding its last docstring paragraph — the "what is active NOW" vs "ever exercised" distinction, which is the useful part — into _set_skills_declarations() or the inline comment. Note ruff won't flag an unused module-level function, so it'll just sit there otherwise.
That's a tidy-up, not a blocker; approving as-is so it isn't gated on another round.
On your point 1 — agreed, leave it. list[str] | None serialising to null and breaking downstream iteration is a real cost against a cosmetic gain, and the residual ambiguity needs a clear that lands on an already-empty set, which no fixture can produce. If #1779 lands and the field starts coming from the tool's result, the question probably resolves itself.
Thanks for flagging the debug_conversation.py import of _activated_skills — that's the kind of breakage that's invisible from this side until the bump. And for filing #1779/#1780 rather than letting them evaporate.
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Summary
_activated_skills()only looked at the current turn's tool calls, soskill_routingwas recomputed from scratch every turn.set_skillskeeps a skill active until it's replaced, so an agent correctly omits a redundant call on a later turn that reuses the same skill — but the scorer forcedskill_routing=Falsewhenever no skill was activated this specific turn, regardless of whether it was already active.Found via
scripts/authoring/debug_conversation.py(gdc-mic-ai-evaluation repo) replayinganalyst-explores-dynamic-currency-conversion: turns t4/t5 both rancreate_adhoc_visualization/create_metricsuccessfully against an already-active skill, yet scored FAIL solely because of this.Fix: replace-with-carry-over, not accumulate
set_skillsREPLACES the active set rather than adding to it — verified against the gen-ai service's skill registry, and stated in the tool's own description. So:A turn that declares nothing inherits the previous turn's set; a turn that declares something drops whatever it left out.
Reporting
skill_routingis conversation-scoped whileactivated_skillsstays per-turn, so a reused-skill turn showsskill_routing=Truealongsideactivated_skills=[]. That reads as a scoring bug to anyone triaging a report, soTurnResult.active_skills(also indetail["turns"][]) now carries the set the credit was actually drawn from. Documented onTurnResult.Test plan
test_..._skill_routing_persists_across_turns— a skill activated in turn 1 and reused without re-declaring in turn 2 is credited on both.test_..._skill_routing_false_when_skill_never_activated— guards against being too lenient; a skill no turn ever activates still fails routing.test_..._skill_routing_false_after_a_later_call_deactivates_it— the case the union version got wrong: t1 activatesmetric, t2 replaces it withvisualization, t3 expectsmetricand declares nothing → correctly FAILs. Verified meaningful by re-injecting the union logic and watching this test fail, then restoring.ruff check/ruff format --checkclean.Known follow-up (not in this PR)
_activated_skills()reads the requested skill names from the tool call's arguments, but the service drops names it doesn't recognise and pulls in declared dependencies — and the tool's result echoes back the authoritative post-replacement set. Reading the result instead would be truer to what actually became active. Pre-existing and a behaviour change, so left separable.Summary by CodeRabbit