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 agentmods add skills/plurigrid/asi/structured-decompnpx skills add plurigrid/asi --skill structured-decompgit clone --depth 1 https://github.com/plurigrid/asiWhat 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 | $0.00021 | $0.00379 |
| Opus 5 | $0.00010 | $0.00189 |
| Sonnet 5 | $0.00004 | $0.00076 |
| Haiku 4.5 | $0.00002 | $0.00038 |
Grade A, and why
structured-decomp 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 today.
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.
What it actually says
Structured Decompositions Skill
Core Concepts
StrDecomp = Functor d: ∫G → C where:
- ∫G = category of elements of shape graph
- C = target category (Graph, FinSet, etc.)
using StructuredDecompositions
# Create decomposition from graph
d = StrDecomp(graph)
# Access components
bags(d) # Local substructures
adhesions(d) # Overlaps
adhesionSpans(d) # Span morphisms
The 𝐃 Functor
Lifts decision problems to decomposition space:
# Define problem as functor
k_coloring(G) = homomorphisms(G, K_k)
# Lift and solve
solution = 𝐃(k_coloring, decomp, CoDecomposition)
(answer, _) = decide_sheaf_tree_shape(k_coloring, decomp)
FPT Complexity
Runtime: O(f(width) × n) where width = max adhesion size
GF(3) Triads
dmd-spectral (-1) ⊗ structured-decomp (0) ⊗ koopman-generator (+1) = 0 ✓
sheaf-cohomology (-1) ⊗ structured-decomp (0) ⊗ colimit-reconstruct (+1) = 0 ✓
References
- Bumpus et al. arXiv:2207.06091
- algebraicjulia.github.io/StructuredDecompositions.jl
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.
- today First seen · 56 lines · 21 tokens per session scan A 644cbf4fa759
structured-decomp is a skill published in the GitHub repository plurigrid/asi (61 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 379 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 2026-09-01.
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