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infra-scaling

Tune and review Langfuse autoscaling for web, web-iso, and web-ingestion. Use for Terraform scale settings, RPM targets, scaling bounds, task counts, cost/performance tradeoffs, or Datadog evidence in the infrastructure repo.

65

Quality

79%

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tessl review fix ./.agents/skills/infra-scaling/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

71%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An impressively actionable body: every workflow step is backed by exact commands, queries, formulas, and file paths, and the validation and PR/ticket procedures are explicit. Its weaknesses are structural — heavy repetition of the ClickHouse-bound guidance and a large amount of catalog-style detail inlined in SKILL.md that would be better split into reference files.

Suggestions

Consolidate the ClickHouse-bound-latency rule, which is restated nearly verbatim in Core Rules, the trace interpretation rules, step 3, and the May 10 learnings, into a single authoritative statement and reference it from the other spots.

Move the Datadog query catalog (per-service metric, trace, and event-loop queries) and the per-environment settings snapshot into a references/ file (e.g., references/datadog-queries.md and references/known-settings.md), keeping SKILL.md as a workflow overview that points to them one level deep.

Add an explicit error-recovery loop after the step 6 validation (e.g., "if tofu fmt -check fails, run tofu fmt on the changed files and re-check") to close the validate→fix→re-run gap in the workflow.

DimensionReasoningScore

Conciseness

Nearly every line carries non-obvious internal facts (autoscaler constants, per-env settings, trace findings) with no padding of known concepts, and the time-sensitive "May 10, 2026 tuning pass" snapshot is explicitly quarantined as point-in-time. However, the ClickHouse-bound-latency rule is restated nearly verbatim in Core Rules, trace interpretation, step 3, and the learnings section, so it could be meaningfully tightened — anchor 3 rather than 4.

3 / 5

Actionability

Fully executable throughout: exact rg and tofu console commands, per-service Datadog query strings, the weighted-load formula, validation commands (tofu fmt -check, git diff --check), and exact tfvars paths cover the common cases copy-paste ready — anchor 5.

5 / 5

Workflow Clarity

A clear 8-step sequence with an explicit validation step (tofu fmt, git diff checks) and explicit blocker-reporting for sandbox and Linear failures. Missing a validate→fix→re-run feedback loop after step 6, so anchor 4 rather than 5; validation is present, so the destructive/batch cap of 3 does not apply.

4 / 5

Progressive Disclosure

Well-sectioned single file with the one external reference (../linear-agent-writes/SKILL.md) clearly signaled as the authority. But ~230 lines inline a full Datadog query catalog, a per-environment settings snapshot, and the Linear write policy — content that clearly belongs in separate reference files — matching anchor 3 rather than 4.

3 / 5

Total

15

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: concrete, third-person, and explicit about both capability and triggers, with good domain-natural trigger terms. It is slightly under-specified on the full range of actions the skill performs, and could add synonyms like "autoscaler" or "ECS capacity" for broader natural-query coverage.

DimensionReasoningScore

Specificity

"Tune and review Langfuse autoscaling for web, web-iso, and web-ingestion" names concrete actions on specific services, but stops at two verbs without enumerating the skill's actual operations (lowering minimums, computing dashboard markers, creating PRs). Fits anchor 4 (several specific actions, minor coverage gaps) better than 5.

4 / 5

Completeness

Explicitly answers both: what ("Tune and review Langfuse autoscaling for web, web-iso, and web-ingestion") and when ("Use for Terraform scale settings, RPM targets...") with concrete trigger phrases — an exact match for anchor 5.

5 / 5

Trigger Term Quality

"Terraform scale settings, RPM targets, scaling bounds, task counts, cost/performance tradeoffs, or Datadog evidence" are phrases users in this repo would naturally say. Missing common synonyms such as "autoscaler", "ECS", "capacity", or "scale up/down", so anchor 4 rather than 5, clearly above 3.

4 / 5

Distinctiveness Conflict Risk

"Langfuse autoscaling" scoped to "the infrastructure repo" is a clear niche with named services and tooling (Terraform, Datadog); no plausible overlap with other skills, matching anchor 5.

5 / 5

Total

18

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository
langfuse/langfuse
Reviewed

Table of Contents

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