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 computer-science-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/computer-science-algorithms)<a href="https://agentmods.dev/skills/pproenca/dot-skills/computer-science-algorithms"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/computer-science-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/computer-science-algorithms"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/computer-science-algorithms.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 | $0.00173 | $0.03300 |
| Opus 5 | $0.00086 | $0.01650 |
| Sonnet 5 | $0.00035 | $0.00660 |
| Haiku 4.5 | $0.00017 | $0.00330 |
Grade A, and why
computer-science-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 Classical Computer Science Algorithms Best Practices
A practitioner-oriented reference for choosing and implementing classical algorithms and data structures correctly. Organized by execution-lifecycle impact: the earliest decisions (asymptotic class, data-structure choice) cascade through everything else, so the rules near the top of the table matter most.
Scope: the patterns that show up in everyday production code review, reasonable interview / contest problems, and the at-scale toolbox (sketches, streaming, distributed primitives) — not an exhaustive cover of CLRS. Topics intentionally outside the current version: network flow, modular arithmetic, Bellman-Ford and Floyd-Warshall as standalone rules, SCC (Tarjan/Kosaraju), computational geometry, FFT, Manacher / Z-function as standalone rules. They're flagged inline in the relevant rules.
Distilled from CLRS (Introduction to Algorithms, 4th ed.), Sedgewick & Wayne (Algorithms, 4th ed., Princeton), Skiena's Algorithm Design Manual, Laaksonen's Competitive Programmer's Handbook, cp-algorithms.com, and the USACO Guide.
When to Apply
Use these rules when:
- Choosing an algorithm or data structure for a new problem ("what's the right way to do X?")
- Reviewing code for hidden O(n²) blowup — repeated
in-checks on lists,pop(0)on lists, string concatenation in loops, naive substring search - Picking a DP state or recurrence, before writing the memoization
- Modeling a problem as a graph (BFS vs Dijkstra vs topological sort)
- Refactoring brute force / naive solutions that work on toy inputs but time out at scale
- Deciding whether greedy applies, or whether DP / branch-and-bound is required
Rule Categories By Priority
| # | Category | Prefix | Impact | Why it cascades |
|---|---|---|---|---|
| 1 | Asymptotic Complexity & Algorithm Selection | comp- |
CRITICAL | Wrong O() class makes every other optimization irrelevant |
| 2 | Data Structure Selection | ds- |
CRITICAL | The container determines which operations are cheap |
| 3 | Sorting & Searching | srch- |
HIGH | Foundation for greedy, two-pointer, sweep-line, binary-search-on-the-answer |
| 4 | Dynamic Programming | dp- |
HIGH | Exponential → polynomial transformations |
| 5 | Graph Algorithms | graph- |
HIGH | Networks, dependencies, routing, scheduling all reduce to graphs |
| 6 | Divide & Conquer / Recursion | divide- |
MEDIUM-HIGH | Logarithmic-factor speedups; stack-depth and recurrence traps |
| 7 | Greedy Algorithms | greedy- |
MEDIUM | Fast when correct, silently wrong when not |
| 8 | String & Sequence Algorithms | str- |
MEDIUM | Pattern matching, parsing, substring queries |
| 9 | Scale & Probabilistic Algorithms | scale- |
MEDIUM | Sketches, streaming, distributed primitives — situational, decisive when they apply |
What ships with it
55 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 13 KB
- assets/templates/_template.md 1.2 KB
- metadata.json 1.2 KB
- references/_sections.md 3.1 KB
- references/comp-amortize-instead-of-worst-casing.md 2.4 KB
- references/comp-derive-recurrences-via-master-theorem.md 2.0 KB
- references/comp-pick-algorithm-class-from-input-bound.md 1.8 KB
- references/comp-prefer-iterative-builders-over-string-concatenation.md 1.8 KB
- references/comp-treat-space-complexity-as-first-class.md 2.1 KB
- references/comp-watch-for-quadratic-blowup-from-membership-in-list.md 1.6 KB
- references/divide-meet-in-the-middle-for-subset-problems.md 2.5 KB
- references/divide-merge-sort-pattern-for-counting-inversions.md 2.3 KB
- references/divide-quickselect-vs-quicksort-partitioning.md 3.0 KB
- references/divide-watch-recursion-depth-and-stack.md 2.5 KB
- references/dp-bitmask-for-small-set-states.md 2.6 KB
- references/dp-define-state-precisely.md 2.8 KB
- references/dp-knapsack-pattern.md 2.6 KB
- references/dp-memoize-overlapping-subproblems.md 2.4 KB
- references/dp-prove-optimal-substructure-before-coding.md 2.6 KB
- references/dp-tabulate-when-recursion-depth-or-order-matters.md 2.6 KB
- references/ds-balanced-bst-or-sorted-container-for-range-queries.md 2.2 KB
- references/ds-deque-for-both-end-operations.md 2.1 KB
- references/ds-fenwick-or-segment-tree-for-mutable-range-queries.md 2.1 KB
- references/ds-hash-map-for-keyed-lookup.md 2.0 KB
- references/ds-heap-for-top-k-and-priority-queues.md 2.0 KB
- references/ds-prefix-sums-for-repeated-range-sums.md 2.1 KB
- references/ds-set-for-uniqueness-and-membership.md 1.9 KB
- references/ds-union-find-for-dynamic-connectivity.md 2.7 KB
- references/graph-bfs-for-unweighted-shortest-path.md 2.9 KB
- references/graph-detect-cycles-during-dfs.md 2.7 KB
- references/graph-dijkstra-for-non-negative-weights.md 2.8 KB
- references/graph-kruskal-or-prim-for-mst.md 3.0 KB
- references/graph-represent-as-adjacency-list-not-matrix.md 2.7 KB
- references/graph-topological-sort-for-dependency-order.md 3.0 KB
- references/greedy-huffman-and-priority-queue-greedies.md 2.6 KB
- references/greedy-interval-merge-and-sweep-line.md 2.9 KB
- references/greedy-prove-exchange-argument-before-using.md 3.0 KB
- references/greedy-sort-by-the-right-key-for-scheduling.md 2.8 KB
- references/scale-aho-corasick-for-multi-pattern-search.md 5.0 KB
- references/scale-bloom-filter-for-probabilistic-membership.md 3.3 KB
- references/scale-consistent-hashing-for-distributed-sharding.md 4.3 KB
- references/scale-count-min-sketch-for-frequency-estimation.md 4.1 KB
- references/scale-external-merge-sort-for-out-of-memory-data.md 4.1 KB
- references/scale-hyperloglog-for-cardinality-estimation.md 3.8 KB
- references/scale-minhash-lsh-for-near-duplicate-detection.md 6.1 KB
- references/scale-reservoir-sampling-for-streams.md 3.9 KB
- references/srch-binary-search-on-sorted-data.md 2.6 KB
- references/srch-counting-and-radix-sort-for-bounded-integer-keys.md 2.2 KB
- references/srch-quickselect-for-k-th-element.md 2.3 KB
- references/srch-two-pointers-on-sorted-data.md 2.4 KB
- references/srch-use-builtin-sort-not-hand-rolled.md 2.2 KB
- references/str-kmp-or-builtin-find-not-naive-search.md 2.6 KB
- references/str-rolling-hash-for-multiple-substring-comparisons.md 2.8 KB
- references/str-suffix-array-or-automaton-for-substring-queries.md 3.1 KB
- references/str-trie-for-prefix-queries.md 3.1 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 · 173 tokens per session scan A 6fc4c8e50334
computer-science-algorithms is a skill published in the GitHub repository pproenca/dot-skills (205 stars, last pushed 24d ago), licensed MIT. It adds 173 tokens to every session and 3,300 once invoked, about $0.0009 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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