klingai-audit-logging
Implement audit logging for Kling AI operations for compliance and security. Use when tracking API usage or preparing for audits. Trigger with phrases like 'klingai audit', 'kling ai audit log', 'klingai compliance log', 'video generation audit trail'.
64
77%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
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npx tessl skill review --optimize ./plugins/saas-packs/klingai-pack/skills/klingai-audit-logging/SKILL.mdQuality
Discovery
89%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a solid description with strong trigger terms and clear completeness, explicitly stating both what the skill does and when to use it. Its main weakness is that the specificity of capabilities could be improved by listing more concrete actions beyond the general 'implement audit logging' and 'tracking API usage'. Overall it performs well for skill selection purposes.
Suggestions
Add more specific concrete actions, e.g., 'Logs API calls, tracks video generation requests, records error events, generates compliance reports for Kling AI operations.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (audit logging for Kling AI operations) and mentions some actions (tracking API usage, preparing for audits), but doesn't list specific concrete actions like what the audit log captures, what format it produces, or what compliance standards it addresses. | 2 / 3 |
Completeness | Clearly answers both 'what' (implement audit logging for Kling AI operations for compliance and security) and 'when' (tracking API usage, preparing for audits) with explicit trigger phrases provided. | 3 / 3 |
Trigger Term Quality | Includes good natural trigger terms: 'klingai audit', 'kling ai audit log', 'klingai compliance log', 'video generation audit trail', plus contextual terms like 'API usage', 'audits', 'compliance', and 'security'. These cover multiple natural variations a user might say. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive — the combination of 'Kling AI' with 'audit logging' creates a very specific niche. The trigger terms are unique enough (e.g., 'klingai audit', 'video generation audit trail') that this is unlikely to conflict with generic audit or generic AI video skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides solid, executable audit logging code for Kling AI with tamper-evident chain hashing, verification, and reporting — all actionable and concrete. However, it lacks an explicit end-to-end workflow showing the sequence of operations (initialize → wrap client → log → verify → report) with validation checkpoints, and the content is somewhat monolithic for its size. The compliance checklist is a nice touch but sits disconnected from the code workflow.
Suggestions
Add a 'Quick Start' or 'Workflow' section at the top showing the explicit sequence: 1) Initialize AuditLogger, 2) Wrap client with KlingAuditClient, 3) Make API calls, 4) Verify chain integrity, 5) Generate report — with validation checkpoints between steps.
Consider moving the report generator and verification functions to a referenced file (e.g., AUDIT_TOOLS.md) to keep the main skill focused on the core logging setup and workflow.
Add an explicit feedback loop for chain verification failure: what to do when verify_audit_chain returns False (e.g., identify tampered entries, restore from backup, alert security team).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The code is mostly efficient and provides real implementation, but there's some verbosity — the full audit report generator and the compliance checklist add bulk that could be trimmed or referenced externally. The code is functional rather than padded with explanations, but the overall length is substantial for what could be a more focused skill. | 2 / 3 |
Actionability | All code is fully executable Python with concrete implementations — the AuditLogger class, KlingAuditClient wrapper, verification function, and report generator are all copy-paste ready with clear interfaces and real logic. | 3 / 3 |
Workflow Clarity | The skill presents individual components (logger, client wrapper, verification, reporting) but lacks an explicit sequenced workflow showing how to set them up end-to-end. There's a verification function but no explicit instruction to run verification after logging operations or a feedback loop for handling broken chains. | 2 / 3 |
Progressive Disclosure | The content is organized into logical sections with clear headers, but it's a monolithic file with ~150 lines of code that could benefit from splitting the report generator and verification into separate referenced files. The external resource links are helpful but the main content is all inline. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
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