ode-solver

Solve ordinary differential equations (initial and boundary value problems). Supports stiff/non-stiff systems, event detection, Hamiltonian/symplectic integration, parameter sweeps, and phase space analysis. Use for any ODE system in physics, engineering, or applied math.

Quality

83%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Quality

Content

78%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.

Highly actionable, executable content with clear workflows and validation/troubleshooting feedback loops. The chief weakness is progressive disclosure: everything lives inline in a long SKILL.md with no bundle references to split detail into.

Suggestions

Move the longer worked examples (e.g. Hamiltonian/symplectic and BVP) into reference files under ./references/ and link to them from a concise overview, keeping only the quick-start IVP inline.

Inline the Validation Checklist into each destructive/batch workflow (e.g. the parameter sweep) so checkpoints appear at the point of use rather than in a separate section.

Trim redundant docstrings/comments in code blocks to lift conciseness toward lean.

Dimension	Reasoning	Score
Conciseness	Lean and assumes competence — no padding about what ODEs are or how scipy works — but the six full inline code examples make the document long enough that a few examples could be trimmed or externalized.	4 / 5
Actionability	Six copy-paste-ready executable examples (IVP, stiff, events, symplectic, BVP, parameter sweep) plus a method-selection table cover the common cases concretely.	5 / 5
Workflow Clarity	Workflows are clearly numbered and labeled, with a Validation Checklist and a Troubleshooting symptom/cause/fix table providing error-recovery feedback loops; the checklist is separated from the workflows rather than inline, leaving minor checkpoint gaps.	4 / 5
Progressive Disclosure	Well-organized sections, but at ~230 lines the entire detailed content (all six worked examples, method guide) is inlined in SKILL.md with no one-level-deep references to separate files, so it functions as a monolith rather than an overview pointing to deeper materials.	3 / 5
	Total	16 / 20 Passed

Description

88%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, specific description that clearly conveys both capability and usage triggers, with comprehensive concrete actions. The main weakness is a slightly broad 'when' clause that could sharpen distinctiveness from neighboring physics skills.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'initial and boundary value problems', 'stiff/non-stiff systems', 'event detection', 'Hamiltonian/symplectic integration', 'parameter sweeps', 'phase space analysis' — giving comprehensive coverage of the skill's capabilities.	5 / 5
Completeness	Explicitly states both what ('Solve ordinary differential equations...Supports...') and when ('Use for any ODE system in physics, engineering, or applied math.') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Strong natural keyword coverage ('ordinary differential equations', 'ODE system', 'initial and boundary value problems', 'physics, engineering, or applied math'), but a few natural synonyms (e.g. 'ODEs', 'numerical integration') are absent.	4 / 5
Distinctiveness Conflict Risk	The ODE-solving niche is clearly distinct from related domains (PDEs, fitting), though the broad 'any ODE system in physics, engineering, or applied math' trigger invites minor overlap with adjacent physics skills.	4 / 5
	Total	18 / 20 Passed

Validation

93%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/physics/ode-solver/SKILL.md
Commit: a820c2f

Reviewed: ~18 hours ago

Table of Contents

Discovery Implementation Validation

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.