implementation-reconstructor
Reconstruct implementation details from a research paper, including algorithms, architecture, pseudocode, data structures, training/runtime phases, missing…
Skill by Siris2314
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/siris2314-implementation-reconstructor
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: testing, data, research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/implementation-reconstructor
What's inside
- Skill name
implementation-reconstructor- Description
- Reconstruct implementation details from a research paper, including algorithms, architecture, pseudocode, data structures, training/runtime phases, missing details, edge cases, and test plans. Use when a user asks how to implement, code, reproduce, or operationalize a paper.
- License
- MIT
- Instructions
- 29 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- openai.yaml · agents/
SKILL.md (first lines)
# Implementation Reconstructor Turn paper method evidence into an implementation plan without pretending missing details are stated. ## Workflow 1. Identify method components and runtime/training phases. 2. Separate explicit paper details from implementation inference. 3. Produce inputs, outputs, data structures, and control flow. 4. Write pseudocode in small functions. 5. Mark missing details. 6. Include a minimal implementation plan and testing strategy. ## Output Sections - Explicit paper algorithm - Inferred implementation design - Pseudocode - Required data structures - Edge cases - Missing details / cannot infer - Unit tests or smoke tests ## Gotchas - Call out missing hyperparameters, exact shapes, storage layout, scheduler, batching, evaluation code, and hardware assumptions. - Label all practical engineering choices that are inferred beyond the paper.
From Siris2314/deep-paper-reader, MIT.
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Analyze research-paper figures, diagrams, plots, tables, ablations, metrics, benchmark evidence, captions, and surrounding text.
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Create compact, provenance-labeled concept cards for terms, acronyms, benchmarks, methods, prerequisites, model families, or UI concept popups.
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paper-term-highlighter
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Identify and highlight significant research-paper terms from parsed paper artifacts and user-confirmed long-term term memory, especially main-method concepts…
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tavily-background
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Gather and synthesize external context for a research paper using Tavily Search, Tavily Research, or cached web artifacts, including concept definitions…
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Interactive research-paper Q&A for a parsed paper workspace.
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paper-evaluator
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Evaluate final reports, serious chat answers, concept cards, or math explanations using deterministic checks and independent LLM-as-a-judge rubrics for…
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Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jul 23, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/Siris2314/deep-paper-reader
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from Siris2314
- 0.603score
math-walkthrough
Siris2314
Parse, typeset, explain, and evaluate research-paper equations, notation, symbols, derivations, losses, objectives, tensor shapes, assumptions, and…
SkillAFreshness: A★ 2Claude Code +9 - 0.512score
figure-table-analysis
Siris2314
Analyze research-paper figures, diagrams, plots, tables, ablations, metrics, benchmark evidence, captions, and surrounding text.
SkillCFreshness: C★ 2Claude Code +9 - 0.512score
concept-card
Siris2314
Create compact, provenance-labeled concept cards for terms, acronyms, benchmarks, methods, prerequisites, model families, or UI concept popups.
SkillCFreshness: C★ 2Claude Code +9 - 0.512score
paper-term-highlighter
Siris2314
Identify and highlight significant research-paper terms from parsed paper artifacts and user-confirmed long-term term memory, especially main-method concepts…
SkillCFreshness: C★ 2Claude Code +9 - 0.507score
tavily-background
Siris2314
Gather and synthesize external context for a research paper using Tavily Search, Tavily Research, or cached web artifacts, including concept definitions…
SkillCFreshness: C★ 2Claude Code +9 - 0.507score
chat-answer
Siris2314
Interactive research-paper Q&A for a parsed paper workspace.
SkillCFreshness: C★ 2Claude Code +9
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Cite this page
implementation-reconstructor skill. Agent Mart. https://agentmart.dev/skills/siris2314-implementation-reconstructor (last updated 2026-10-24)