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subsystem-summary-of-simulation

read this skill for a token-efficient summary of the simulation subsystem

50

Quality

54%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./.claude/skills/subsystem-summary-of-simulation/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%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 body is a well-organized, accurate-feeling, information-dense reference for the simulation subsystem with clearly sequenced internal flows. Its main weaknesses are the total absence of executable usage guidance (no code snippet or command example) and the inlining of exhaustive API detail into SKILL.md, which works against the skill's stated token-efficiency purpose. Some duplication between the Key Files, Control flow, and Key Data Flows sections could be trimmed.

Suggestions

Add a short quick-start example — e.g., a code snippet creating a Simulation via Topologies::core(...) with crankAllNodes/haveAllExternalized, or the loadgen HTTP command with a GeneratedLoadConfig — to make the reference actionable rather than purely descriptive.

Move the exhaustive per-member/per-function listings (especially ApplyLoad and TxGenerator) into one-level-deep reference files, keeping the overview, key flows, and threading model in SKILL.md to honor the skill's 'token-efficient' claim.

Deduplicate the LoadGenerator 'Control flow' list against the 'Key Data Flows' section, and fold the 'Key Files' list into the per-class sections it repeats.

DimensionReasoningScore

Conciseness

The body is dense, bullet-style, repo-specific fact (members, signatures, constants, flows) with essentially no padding and no explanation of concepts Claude already knows — matching anchor 4 ('Efficient; minor instances of over-explanation that could be trimmed'). It is not a 5 because of duplication (the 'Key Files' list repeats the per-class sections, and LoadGenerator's 'Control flow' restates the 'Key Data Flows' section) and because ~24KB inlined in SKILL.md undercuts the skill's own 'token-efficient' claim; not a 3 because there is no genuinely unnecessary explanatory prose.

4 / 5

Actionability

The reference is concrete and specific — named functions, parameters, constants like STEP_MSECS = 100, and per-mode dispatch — but it contains no executable guidance: no usage snippet (e.g., a Topologies::core(...) test setup with haveAllExternalized), no loadgen HTTP command example, no build/run instructions. This matches anchor 3 ('Some concrete guidance but incomplete; missing key details'); it is not a 4 because nothing in the document is copy-paste runnable or tells the reader how to actually use the subsystem.

3 / 5

Workflow Clarity

The three internal processes (Simulation node lifecycle, LoadGenerator submission loop, ApplyLoad benchmark flow) are each presented as clear, coherent numbered sequences with the key state transitions (generateLoad → start → 100ms steps → waitTillComplete → reset), matching anchor 4 ('Clear sequence with most checkpoints present'). It is not a 5 because there are no explicit validation checkpoints or error-recovery guidance beyond the mention of txBAD_SEQ retries, and not a 3 because the sequences have no gaps and are easy to follow.

4 / 5

Progressive Disclosure

Section headers are clear and navigation within the file is easy, but 280+ lines of per-member and per-function API reference (e.g., ApplyLoad's ~30 functions, every Simulation member) are inlined in SKILL.md rather than split into reference files — matching anchor 3 ('content that should be separate is inline', e.g. 200 lines of API reference that could be in a separate file). It is not a 2 because the structure is genuinely well-organized with clear section headers, and not a 4 because the exhaustive detail would be better placed in one-level-deep reference files with a leaner overview in SKILL.md.

3 / 5

Total

14

/

20

Passed

Description

45%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.

The description names its domain and a single action but is written as an imperative instruction to the reader rather than a third-person capability description. It omits any 'use when' trigger guidance and the natural keywords (loadgen, benchmark, topologies) that would let a user — or Claude — reliably select this skill. It also under-describes the subsystem's actual scope relative to the body's content.

Suggestions

Rewrite in third person with concrete actions, e.g.: "Summarizes the stellar-core simulation subsystem: Simulation orchestration, Topologies factories, LoadGenerator, TxGenerator, and ApplyLoad benchmarking. Use when asked about simulation, load generation, or benchmarking code in stellar-core."

Add an explicit trigger clause ("Use when...") naming natural user phrasings such as load generation, loadgen, network simulation, topologies, or benchmarking, which would also lift completeness and trigger-term quality.

Include the subsystem's concrete components (Simulation, Topologies, LoadGenerator, ApplyLoad) in the description so the skill is distinguishable from generic simulation or summary skills.

DimensionReasoningScore

Specificity

The description names the domain ("simulation subsystem") and a single generic action ("summary") — matching the anchor 'Names the domain but actions are minimal or generic'. Additionally, the imperative framing "read this skill" addresses the reader directly (second-person equivalent of 'You can use this'), which per the judging guidelines reduces the specificity score by 1 from its natural boundary 2–3 fit. It is not a 1 because the domain is at least named, and not a 3 because no concrete capabilities (load generation, topologies, benchmarking) are listed.

2 / 5

Completeness

The 'what' is reasonably clear ("a token-efficient summary of the simulation subsystem"), but there is no 'when' — no 'Use when...' clause or equivalent trigger guidance, which per the guidelines caps completeness at 3. This matches anchor 3 ('Has a clear what but when is missing or only weakly implied'); it is not a 4/5 because 'when' is entirely absent, and not a 2 because the 'what' is not vague.

3 / 5

Trigger Term Quality

"simulation" and "summary" are relevant natural keywords, but the description misses common variations and synonyms a user would actually say — "load generator", "loadgen", "topologies", "benchmark", "network simulation", "test setup". This matches anchor 3 ('Some relevant keywords but missing common variations or synonyms', e.g. 'Works with PDF files'); it is not a 4 because several natural terms are absent, and not a 2 because more than generic language is present.

3 / 5

Distinctiveness Conflict Risk

"simulation subsystem" is somewhat specific within a codebase context, but without qualifying terms (stellar-core, load generation, benchmarking) it could still overlap with other simulation- or summary-oriented skills. This matches anchor 3 ('Somewhat specific but could still overlap with similar skills'); it is not a 4 because no distinct trigger phrases delineate a clear niche, and not a 2 because the domain is narrower than generic 'document files'.

3 / 5

Total

11

/

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
stellar/stellar-core
Reviewed

Table of Contents

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