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 Zhang-Henry/CoEvoSkills --skill evo-lean-induction-proofgit clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkillsWrote 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/zhang-henry/coevoskills/evo-lean-induction-proof)<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/evo-lean-induction-proof"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-lean-induction-proof/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/evo-lean-induction-proof"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-lean-induction-proof.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00080 | $0.01110 |
| Opus 5 | $0.00040 | $0.00555 |
| Sonnet 5 | $0.00016 | $0.00222 |
| Haiku 4.5 | $0.00008 | $0.00111 |
Grade A, and why
evo-lean-induction-proof 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 11d 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lean 4 Induction Proof Skill
Overview
This skill handles Lean 4 proof completion tasks where:
- A recursive sequence is defined (e.g., partial sums of a geometric series)
- A bound must be proved for all natural numbers
- The proof environment uses Heather Macbeth's Math2001 library tactics
Key Proof Strategy
Stronger Helper Lemma Pattern:
When proving S n ≤ bound for a recursive sequence, direct induction often
fails because the inductive hypothesis S k ≤ bound is too weak. Instead:
- Find the closed-form expression for S n (e.g.,
S n = 2 - 1/2^n) - Prove
S m = closed_formbysimple_induction - Rewrite the goal with the closed form
- Prove the bound using positivity of the remainder term
Tactic Reference (Math2001 library):
simple_induction n with k IH— standard induction with push_castsimp [S]— unfold the recursive definitionrw [IH]— apply induction hypothesisrw [pow_succ]— rewrite2^(k+1)as2^k * 2ring— close algebraic goals over commutative ringsnorm_num— numeric normalizationlinarith— linear arithmeticaddarith— weaker linear arithmetic (from library)positivity— prove positivity goals (from Mathlib)div_pos,pow_pos— positivity lemmas for division and powers
Compilation:
- Use
lake env lean solution.lean(notleandirectly, notlake build) - No output = success; any output indicates errors or warnings
- Warnings must be treated as errors (remove unused variables)
- Avoid
field_simp— may not be available in all configurations
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-lean-induction-proof/scripts')
from utils import run_end_to_end, validate_solution, read_template, get_prefix_lines, write_solution, compile_lean
# End-to-end: reads template, generates proof, writes, compiles, validates
result = run_end_to_end(
workspace_dir='/app/workspace',
solution_file='solution.lean',
proof_start_line=15, # line where proof body starts
timeout=300
)
print(f"Success: {result['success']}")
if not result['success']:
print(f"Issues: {result['issues']}")
# Validation only (after manual proof writing)
lines = read_template('/app/workspace/solution.lean')
prefix = get_prefix_lines(lines, 15)
val = validate_solution('/app/workspace', 'solution.lean', prefix, 15)
print(f"Valid: {val['valid']}, Issues: {val['issues']}")
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 105 lines · 80 tokens per session scan A 66eb9327da8e
evo-lean-induction-proof is a skill published in the GitHub repository Zhang-Henry/CoEvoSkills (66 stars, last pushed 21d ago), licensed Apache-2.0. It adds 80 tokens to every session and 1,110 once invoked, about $0.0004 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 2026-08-30.
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