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SKILL verified Apache-2.0 Self-run

Data Structures

skill-kentoshimizu-sw-agent-skills-data-structures · by KentoShimizu

Select data structures using explicit access patterns, mutation behavior, memory limits, and concurrency constraints. Use when implementation correctness or performance depends on choosing between alternatives (array/map/heap/tree/queue/set) under real workload assumptions; do not use for persistence schema or deployment topology decisions.

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Install

$ agentstack add skill-kentoshimizu-sw-agent-skills-data-structures

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Data Structures

Overview

Use this skill to choose data structures with explicit tradeoffs, then justify the choice with workload assumptions and failure modes.

Scope Boundaries

  • Use this skill when the task matches the trigger condition described in description.
  • Do not use this skill when the primary task falls outside this skill's domain.

Inputs To Gather

  • Required operations (lookup, insert, delete, scan, range, top-k).
  • Read/write ratio and mutation frequency.
  • Data volume now and forecast at peak.
  • Latency/memory constraints and concurrency model.

Deliverables

  • Candidate structure comparison with tradeoffs.
  • Selected structure and rationale tied to workload.
  • Risk list (memory blowup, contention, degeneration cases).
  • Verification plan (microbenchmarks and edge-case tests).

Quick Decision Examples

  • Frequent key lookup + updates: hash map (+ collision strategy).
  • Sorted range queries: balanced tree or ordered index.
  • Top-N / priority scheduling: heap.
  • FIFO work pipeline: queue (bounded if backpressure is needed).
  • Membership checks with low memory: bitset/Bloom filter (with false-positive caveat).

Quality Standard

  • Choice is tied to actual operation mix, not preference.
  • Complexity claims include worst/average behavior assumptions.
  • Memory growth and peak usage are estimated.
  • Concurrency implications are explicit (lock scope, contention hotspots).

Workflow

  1. Define workload model and required guarantees.
  2. Enumerate feasible structures at the same abstraction level.
  3. Compare complexity, memory, and concurrency behavior.
  4. Select one and document rejection reasons for others.
  5. Define benchmark and edge-case validation plan.

Failure Conditions

  • Stop when workload assumptions are missing or contradictory.
  • Stop when chosen structure cannot satisfy mandatory operations.
  • Escalate when memory or contention risk is unbounded at target scale.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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