CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

distributed-tracing

Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.

60

Quality

75%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/observability-monitoring/skills/distributed-tracing/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

51%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.

The skill is well-structured with exemplary progressive disclosure — a lean overview with one well-signaled, real reference file — but the body itself lacks executable depth and any ordered implementation workflow, with most guidance given as high-level directives rather than commands or code. Redundant restatement of the description across three sections also dilutes token efficiency.

Suggestions

Replace the intro/Purpose/When-to-Use redundancy with one short section, freeing tokens for the missing implementation sequence (instrument services → deploy collector → verify traces in the backend).

Make the troubleshooting and best-practice bullets executable: give the actual commands or config snippets (e.g., how to check the collector endpoint, how to switch to a BatchSpanProcessor, what sampling config to change).

Add validation checkpoints to the workflow, such as how to confirm a trace appears end-to-end after instrumentation, so errors can be caught before moving on.

DimensionReasoningScore

Conciseness

The body is mostly tight (no basic-concept explanations, one focused code block), but the opening line, "Purpose", and "When to Use" sections all restate the same intent three times, and several Best Practices items ("Document instrumentation standards", "Set up alerts") carry little actionable content. This matches anchor 3 ('mostly efficient but includes some unnecessary explanation or could be tightened') better than 4, where over-explanation would be only minor.

3 / 5

Actionability

There is one complete executable Python snippet (correlated logging) and some concrete numbers (1-10% sampling, <1% CPU), but the bulk of the guidance — "Check collector endpoint", "Reduce sampling rate", "Propagate context across all service boundaries" — gives no commands or code and no setup steps in the body. This sits between anchor 2 (high-level hints, missing steps) and anchor 4 (mostly executable), landing on 3: some concrete guidance but incomplete.

3 / 5

Workflow Clarity

There is no sequenced implementation workflow at all — the body offers use cases, best practices, and symptom→action troubleshooting lists, but never an ordered set of steps (instrument → deploy collector → verify traces) with validation checkpoints. That matches anchor 2 ('rough sequence present but many gaps; validation absent') rather than 3, which requires steps to be listed; the actual sequence is deferred entirely to references/details.md.

2 / 5

Progressive Disclosure

The body is a concise overview with a single, clearly signaled, one-level-deep pointer — "Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient" — and that file actually exists and contains the deep content (Jaeger setup, instrumentation, context propagation). Scoring against the real bundle structure, this matches anchor 5 (clear overview, well-signaled one-level reference, appropriate split); it is not 4 because nothing that belongs in the reference is inlined and the navigation trigger is explicit.

5 / 5

Total

13

/

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: explicit what and when with concrete trigger phrases, named tools, and a distinctive niche. Its only weakness is trigger-term breadth — missing natural synonyms like "traces", "spans", or "trace a request" that users would commonly say.

DimensionReasoningScore

Specificity

The description names concrete actions ("Implement distributed tracing", "track requests across microservices", "identify performance bottlenecks") plus specific tools (Jaeger, Tempo). It lists several specific actions with minor coverage gaps (no mention of analyzing traces or visualizing), matching the anchor-4 example's shape; it is not comprehensive enough for 5.

4 / 5

Completeness

It explicitly answers both: what ("Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks") and when ("Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems") with concrete trigger phrases — a direct match for the anchor-5 example. Not 4 because the 'when' clause is already fully explicit with concrete triggers, not merely adequate.

5 / 5

Trigger Term Quality

Natural phrases like "debugging microservices", "analyzing request flows", "implementing observability", and tool names (Jaeger, Tempo) are terms users would actually say. Common variations such as "traces", "spans", or "trace a request" are missing, which is exactly the 'good coverage, a few natural terms missing' anchor 4; not 3 because coverage is broad and domain-accurate, not 5 because synonyms/aliases are absent.

4 / 5

Distinctiveness Conflict Risk

A clear niche (distributed tracing with named backends Jaeger/Tempo) with distinct triggers; minimal overlap with adjacent observability skills since the description does not claim metrics or logging. Matches anchor 5 ('clear niche with distinct triggers; minimal conflict risk') rather than 4, which requires minor overlap risk.

5 / 5

Total

18

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

wshobson/agents

Path

plugins/observability-monitoring/skills/distributed-tracing/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.