Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jimmc414/claude-code-plugin-marketplace --skill verify-solution-propertiesgit clone --depth 1 https://github.com/jimmc414/claude-code-plugin-marketplaceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/verify-solution-properties)<a href="https://agentmods.dev/skills/jimmc414/claude-code-plugin-marketplace/verify-solution-properties"><img src="https://agentmods.dev/badge/skills/jimmc414/claude-code-plugin-marketplace/verify-solution-properties.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.00648 |
| Opus 5 | $0.00012 | $0.00324 |
| Sonnet 5 | $0.00005 | $0.00130 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
verify-solution-properties scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
verify-solution-properties
When to Use
- After solver/algorithm produces result
- When solution is complex but verification is simple
- Testing optimizers and search algorithms
- Building confidence in results
When NOT to Use
- Verification as expensive as solving
- Trivially correct results
- No independent definition of "correct"
The Pattern
Write a separate function that checks if a proposed solution satisfies all requirements.
def solve(problem):
"""Find a solution (complex algorithm)."""
...
return solution
def is_valid_solution(solution, problem):
"""Check if solution is valid (simple verification)."""
return (satisfies_constraint_1(solution, problem) and
satisfies_constraint_2(solution, problem) and
covers_all_requirements(solution, problem))
# Use both together
solution = solve(problem)
assert is_valid_solution(solution, problem)
Example (from pytudes)
# sudoku.py - solution verification
def solved(values):
"""A puzzle is solved if each unit is a permutation of digits 1-9."""
def unitsolved(unit):
return set(values[s] for s in unit) == set(digits)
return values is not False and all(unitsolved(unit) for unit in unitlist)
# More detailed solution check (Sudoku.ipynb)
def is_solution(solution, puzzle):
"""Is this proposed solution to the puzzle actually valid?"""
return (solution is not None and
# Solution respects original puzzle constraints
all(solution[s] in puzzle[s] for s in squares) and
# Each unit is a permutation of 1-9
all({solution[s] for s in unit} == set(digits)
for unit in all_units))
# SET.py - game rule verification
def is_set(cards):
"""Are these 3 cards a valid SET?"""
for f in range(4): # 4 features
values = {card[f] for card in cards}
if len(values) == 2: # 2 distinct values = not a set
return False
return True
# Cryptarithmetic solution verification
def valid(pformula):
"""A formula is valid iff it has no leading zero and evaluates to True."""
try:
return (not leading_zero(pformula)) and (eval(pformula) is True)
except ArithmeticError:
return False
# Usage pattern
for digits in permutations(...):
solution = substitute(digits, formula)
if valid(solution): # Independent verification
yield solution
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 90 lines · 23 tokens per session scan A c1c3075fa624
verify-solution-properties is a skill published in the GitHub repository jimmc414/claude-code-plugin-marketplace (4 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 648 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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