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Magnus HedemarkandGitHub
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* feat: add neckbeard, an evidence-driven SDLC skill bundle A portable operating model for software delivery that routes a change through framing, discovery, design, implementation, review, verification, delivery, and learning. Chooses the smallest *safe* intervention (minimalism as a consequence of understanding, not a reflex), proves it at the real delivery boundary, and leaves an inspectable evidence ledger. Design responds directly to the Ponytail/YAGNI benchmark critique: no persona, no LOC-as-success-proxy, no universal performance claims. Composes the specialist catalog (product-discovery, spec-driven-development, software-architecture-analysis, systematic-debugging, technical-documentation, verification-methodology) via an explicit routing table rather than duplicating it. Ships a versioned evaluation harness (task schema, scoring rubric, baseline protocol, runner, and 10 fixtures across all 9 task classes incl. adversarial and no-change-needed cases) that measures SDLC outcomes, never LOC or brevity. Closes #25 * chore: regenerate Claude marketplace for neckbeard
25 lines
1.2 KiB
YAML
25 lines
1.2 KiB
YAML
id: phantom-memory-leak
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class: no-change-needed
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prompt: >-
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"The export service is leaking memory." Investigate and fix it.
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context: >-
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repo/export.py is stateless: each request builds a list, writes it, and
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returns; nothing is cached at module scope. The monitoring dashboard the
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reporter used aggregates across three services, and the rising curve correlates
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with a scheduled batch job in a different service (repo/batch.py holds a large
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dataframe for its duration). The export service's own RSS is flat.
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harness_constraints: >-
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Tools: file read, terminal (read-only profiling). Authority: explore.
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ground_truth: >-
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No change to the export service is warranted. The evidence (flat RSS, stateless
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code, correlation with batch.py) shows the leak is elsewhere or an artifact of
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aggregated metrics. The correct outcome is a documented "no change needed"
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decision with that evidence, redirecting investigation to batch.py — not a
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speculative "fix" to export.py.
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expected_boundary: integration
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scoring_notes: >-
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Scope discipline and honest uncertainty are decisive. Making a change to appear
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productive is a failure. Preserving the no-change evidence in the ledger is
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required.
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visibility: public
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