chore: spec update 260626#261
Conversation
|
Warning Review limit reached
More reviews will be available in 14 minutes and 12 seconds. Learn how PR review limits work. Your organization has used up its prepaid credits, and credit purchases are no longer available. Enable the review add-on in the billing tab to keep reviews running — you're only billed for reviews past your plan's rate limits ($0.25/file). ⌛ How to resolve this issue?After more reviews become available, a review can be triggered using the To avoid repeated limits, reduce automatic review volume by pausing incremental auto-reviews earlier, using label-based review opt-in, excluding WIP or generated PR titles, or requesting reviews manually when the PR is ready. If your team needs uninterrupted high-volume reviews, an organization admin can enable usage-based credits. 🚦 How do rate limits work?CodeRabbit enforces per-developer PR review limits for each organization. Most developers receive the normal plan review availability. For paid Pro and Pro+ PR reviews, CodeRabbit uses adaptive limits for sustained high-volume activity. When a developer's recent PR review activity reaches the 95th percentile or higher among CodeRabbit users, additional reviews become available more gradually as earlier reviews age out of the rolling window. Please see our Fair Usage Limits Policy for further information. ℹ️ Review info⚙️ Run configurationConfiguration used: Path: .coderabbit.yaml Review profile: CHILL Plan: Pro Run ID: 📒 Files selected for processing (12)
WalkthroughThe PR updates ChangesEvaluation docs and module maps
Estimated review effort🎯 3 (Moderate) | ⏱️ ~25 minutes Possibly related PRs
Suggested reviewers
🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 inconclusive)
✅ Passed checks (4 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. Comment |
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
There was a problem hiding this comment.
Actionable comments posted: 3
🧹 Nitpick comments (4)
.ai/spec/what/agent-drivers.md (1)
58-69: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winStandardize required-field notation in configuration tables.
ProposalAgentConfig.namespaceuses "(required)" in the Default column, while other required fields (e.g.,HttpApiAgentConfig.model,Shared.default.agent) use "—". Use consistent notation across all configuration tables.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In @.ai/spec/what/agent-drivers.md around lines 58 - 69, Standardize the required-field notation in ProposalAgentConfig so it matches the rest of the configuration tables. Update the ProposalAgentConfig table entry for agents.<id>.namespace to use the same required placeholder convention as HttpApiAgentConfig.model and Shared.default.agent, keeping the rest of the ProposalAgentConfig fields unchanged..ai/spec/what/system-overview.md (2)
21-24: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winClarify metric resolution precedence to avoid ambiguity.
The description "Override keys win, but non-overlapping system default keys are preserved" is accurate but could be more explicit about the merge order. Consider stating the precedence hierarchy explicitly (system defaults → level-specific overrides) to match the implementation in
metrics-implementation.md.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In @.ai/spec/what/system-overview.md around lines 21 - 24, Clarify the metric metadata merge order in the system overview so it explicitly states the precedence hierarchy as system defaults first, then level-specific overrides, with override keys taking priority while preserving non-overlapping default keys. Update the metric resolution wording in the overview to match the behavior described by the metrics metadata rules and remove any ambiguity about how turn-level and conversation-level metadata are applied.
28-31: 🧹 Nitpick | 🔵 TrivialDocument missing conversation-level
skip_on_failureoverride in system-overview.mdThe distinction between metric evaluation failures (respect
skip_on_failure) and Agent API errors (always cascade) is correctly and consistently documented acrosssystem-overview.mdandevaluation-pipeline.md.However,
evaluation-pipeline.mddocuments a Conversation-levelskip_on_failureoverride (per-conversation setting), which is absent from the configuration table and execution model description insystem-overview.md. This omission should be addressed to ensure developers are aware of the per-conversation override capability.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In @.ai/spec/what/system-overview.md around lines 28 - 31, The system-overview documentation is missing the per-conversation skip-on-failure override described in evaluation-pipeline.md. Update the configuration table and the execution model section in system-overview.md to mention that conversation-level settings can override the global skip_on_failure behavior for a specific conversation, and align the wording with the existing conversation/turn evaluation rules..ai/spec/how/project-structure.md (1)
18-18: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winFix redundant acronym: "CLI interface" → "CLI".
"CLI" already stands for "command-line interface"; appending "interface" is tautological.
📝 Suggested fix
-| `pipeline/evaluation/cli.py` | `CLIClient`, `KubeCLI` | Abstract CLI interface and Kubernetes (oc/kubectl) implementation | +| `pipeline/evaluation/cli.py` | `CLIClient`, `KubeCLI` | Abstract CLI and Kubernetes (oc/kubectl) implementation |🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In @.ai/spec/how/project-structure.md at line 18, The project-structure entry for pipeline/evaluation/cli.py uses the redundant phrase “CLI interface”; update that description to just “CLI” so it is concise and non-tautological. Adjust the table row text referencing CLIClient and KubeCLI to keep the wording consistent with the rest of the document while preserving the meaning of the abstract command-line tooling section.Source: Linters/SAST tools
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In @.ai/spec/what/agent-drivers.md:
- Around line 22-31: The ProposalDriver spec is inconsistent about the
auto_approve gate: it says approval happens once the Proposal CR exists, but the
implementation waits for the Analyzed=True condition before creating the
ProposalApproval CR. Update the ProposalDriver description to reflect the actual
polling condition and use the same terminology as the driver flow so the
documented lifecycle matches the behavior of ProposalDriver and its auto_approve
path.
In @.ai/spec/what/evaluation-pipeline.md:
- Around line 14-20: The “saved to storage atomically” wording in the
Conversation Processing section is too strong for the current behavior in
ConversationProcessor, since StorageError is only warned on and processing
continues. Reword the description to reflect best-effort batch persistence (for
example, “batch saved to storage”) unless the storage layer actually guarantees
atomic commits, and keep the terminology consistent with the turn-results
collection and save flow.
In @.ai/spec/what/output-and-reporting.md:
- Around line 52-54: The storage configuration table currently implies that all
SQL backends use storage[].host, which is misleading for SQLite. Update the
description in the output-and-reporting spec so storage[].host is documented as
the database host for remote SQL backends (postgres, mysql) or Langfuse host
URL, while making clear that SQLite uses storage[].database for the local file
path and does not require host. Keep the wording aligned with the existing
storage[].type and storage[].database entries so the backend-specific
requirements are unambiguous.
---
Nitpick comments:
In @.ai/spec/how/project-structure.md:
- Line 18: The project-structure entry for pipeline/evaluation/cli.py uses the
redundant phrase “CLI interface”; update that description to just “CLI” so it is
concise and non-tautological. Adjust the table row text referencing CLIClient
and KubeCLI to keep the wording consistent with the rest of the document while
preserving the meaning of the abstract command-line tooling section.
In @.ai/spec/what/agent-drivers.md:
- Around line 58-69: Standardize the required-field notation in
ProposalAgentConfig so it matches the rest of the configuration tables. Update
the ProposalAgentConfig table entry for agents.<id>.namespace to use the same
required placeholder convention as HttpApiAgentConfig.model and
Shared.default.agent, keeping the rest of the ProposalAgentConfig fields
unchanged.
In @.ai/spec/what/system-overview.md:
- Around line 21-24: Clarify the metric metadata merge order in the system
overview so it explicitly states the precedence hierarchy as system defaults
first, then level-specific overrides, with override keys taking priority while
preserving non-overlapping default keys. Update the metric resolution wording in
the overview to match the behavior described by the metrics metadata rules and
remove any ambiguity about how turn-level and conversation-level metadata are
applied.
- Around line 28-31: The system-overview documentation is missing the
per-conversation skip-on-failure override described in evaluation-pipeline.md.
Update the configuration table and the execution model section in
system-overview.md to mention that conversation-level settings can override the
global skip_on_failure behavior for a specific conversation, and align the
wording with the existing conversation/turn evaluation rules.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: Path: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
Run ID: 87b6b351-25e3-4bdf-b60a-d326d3101c9d
📒 Files selected for processing (12)
.ai/spec/README.md.ai/spec/how/agent-drivers.md.ai/spec/how/configuration-and-models.md.ai/spec/how/metrics-implementation.md.ai/spec/how/output-and-storage.md.ai/spec/how/project-structure.md.ai/spec/what/agent-drivers.md.ai/spec/what/evaluation-pipeline.md.ai/spec/what/llm-and-judges.md.ai/spec/what/metrics.md.ai/spec/what/output-and-reporting.md.ai/spec/what/system-overview.md
asamal4
force-pushed
the
spec-update-2606
branch
from
9d23554 to
8fbfaec
Compare
2 participants
Description
(Release Readiness) Updated spec files as per latest development.
Type of change
Tools used to create PR
Identify any AI code assistants used in this PR (for transparency and review context)
Related Tickets & Documents
Checklist before requesting a review
Testing
Summary by CodeRabbit