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 pproenca/dot-skills --skill codebase-comprehension-algorithmsgit clone --depth 1 https://github.com/pproenca/dot-skillsWrote 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/pproenca/dot-skills/codebase-comprehension-algorithms)<a href="https://agentmods.dev/skills/pproenca/dot-skills/codebase-comprehension-algorithms"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/codebase-comprehension-algorithms/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/pproenca/dot-skills/codebase-comprehension-algorithms"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/codebase-comprehension-algorithms.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00229 | $0.03642 |
| Opus 5 | $0.00114 | $0.01821 |
| Sonnet 5 | $0.00046 | $0.00728 |
| Haiku 4.5 | $0.00023 | $0.00364 |
Grade A, and why
codebase-comprehension-algorithms 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 5d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Community Codebase Comprehension And Domain Mapping Algorithms Best Practices
A practitioner-oriented reference of the algorithms that work for mapping a codebase into understandable feature/business domains. Most of these techniques live in the Software Architecture Recovery and Mining Software Repositories literatures and are invisible to working engineers — yet they're the right tools for the job a coding agent is asked to do every day: "what does this codebase do, and where?"
The 47 rules are organized by execution-lifecycle impact: a wrong decision early in the pipeline (which graph to build, which identifiers to keep) propagates through everything downstream. The three CRITICAL categories (graph-, clust-, valid-) are the ones a wrong call cannot be recovered from later. Read them first.
Scope: proven algorithms with peer-reviewed citations or canonical books — Newman Networks, Leskovec-Rajaraman-Ullman Mining of Massive Datasets, Ganter-Wille Formal Concept Analysis, plus 40+ ICSE / FSE / TSE / PNAS / JMLR papers. No tutorial sites, no Stack Overflow, no marketing posts. Deliberately deferred to a future version: GNN/CodeBERT/code2vec (not "proven over decades" yet) and refactoring-recipe stuff (covered by sibling skills like react-refactor and typescript-refactor).
When to Apply
Use these rules when:
- Onboarding an agent into an unfamiliar codebase: "explain what this codebase does, by domain"
- Producing an architecture map: "what are the main subsystems and how do they connect?"
- Locating a feature: "which files implement payments / authentication / search?"
- Reviewing a refactor: "did this change respect the architectural boundaries?"
- Detecting architectural debt: "what files have surprising coupling?"
- Validating an existing decomposition: "does the README's architecture match the code?"
- Picking algorithms for any of the above — the user wants something that's proven, not vibes
Rule Categories By Priority
What ships with it
51 files 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.
- AGENTS.md 16 KB
- assets/templates/_template.md 2.5 KB
- metadata.json 2.5 KB
- references/_sections.md 6.0 KB
- references/arch-acdc-subgraph-patterns.md 7.2 KB
- references/arch-bunch-with-mq-fitness.md 7.3 KB
- references/arch-dsm-partitioning.md 7.3 KB
- references/arch-limbo-information-bottleneck.md 7.9 KB
- references/arch-reflexion-model.md 7.6 KB
- references/clust-hdbscan-density-based.md 6.3 KB
- references/clust-infomap-mdl-on-random-walks.md 6.3 KB
- references/clust-leiden-not-louvain.md 6.3 KB
- references/clust-mcl-markov-clustering.md 6.1 KB
- references/clust-spectral-laplacian-fiedler.md 6.5 KB
- references/clust-stochastic-block-model.md 6.4 KB
- references/clust-walktrap-short-random-walks.md 6.2 KB
- references/evol-filter-large-commits.md 7.3 KB
- references/evol-logical-coupling-as-architectural-signal.md 8.1 KB
- references/evol-mine-cochange-with-lift-and-confidence.md 7.5 KB
- references/evol-temporal-decay-on-edge-weights.md 6.9 KB
- references/graph-bipartite-file-term-for-joint-structure.md 7.1 KB
- references/graph-collapse-sccs-before-clustering.md 6.1 KB
- references/graph-combine-signals-in-multilayer-graphs.md 6.5 KB
- references/graph-filter-omnipresent-utilities-before-clustering.md 5.1 KB
- references/graph-pick-edge-type-by-question-asked.md 5.5 KB
- references/graph-weight-edges-by-information-content.md 5.6 KB
- references/info-mdl-for-model-selection.md 7.3 KB
- references/info-mutual-information-as-coupling.md 7.3 KB
- references/info-naturalness-of-code-as-quality-signal.md 8.0 KB
- references/info-normalized-compression-distance.md 7.3 KB
- references/lex-build-programming-language-stop-words.md 6.3 KB
- references/lex-expand-abbreviations-with-context.md 7.0 KB
- references/lex-extract-verb-object-pattern-from-method-names.md 7.0 KB
- references/lex-split-identifiers-with-samurai.md 6.6 KB
- references/lex-stem-versus-subword-tokenization.md 6.4 KB
- references/lex-tf-idf-and-bm25-on-identifiers.md 6.2 KB
- references/rank-betweenness-centrality-for-bottlenecks.md 6.9 KB
- references/rank-hits-hubs-and-authorities.md 6.4 KB
- references/rank-pagerank-for-module-importance.md 6.5 KB
- references/rank-textrank-for-cluster-labels.md 7.7 KB
- references/topic-hdp-for-nonparametric-topic-count.md 6.9 KB
- references/topic-lda-on-source-code.md 7.4 KB
- references/topic-lsi-svd-on-term-document.md 6.3 KB
- references/topic-nmf-non-negative-factorization.md 6.8 KB
- references/topic-pick-topic-count-by-coherence-not-perplexity.md 7.7 KB
- references/valid-ablate-each-input-signal.md 7.4 KB
- references/valid-adjusted-rand-index-and-nmi.md 7.5 KB
- references/valid-be-aware-of-resolution-limit.md 7.8 KB
- references/valid-cochange-prediction-as-ground-truth-proxy.md 7.9 KB
- references/valid-consensus-clustering-for-stability.md 7.3 KB
- references/valid-mojofm-as-software-clustering-distance.md 7.3 KB
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.
- 5d ago First seen · 146 lines · 229 tokens per session scan A 8e10ac7a8c53
codebase-comprehension-algorithms is a skill published in the GitHub repository pproenca/dot-skills (205 stars, last pushed 24d ago), licensed MIT. It adds 229 tokens to every session and 3,642 once invoked, about $0.0011 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 2026-09-03.
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