systematic-research
Skill14 starsChanged 4 months agoMITView on GitHub
Use when researching a topic from web or academic sources, gathering evidence, building a knowledge base, or identifying research gaps with source provenance.
In this repository9 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- writing-skillsSkill
- academic-pptx-skillSkill
- analyze-plotSkill
- paper-extractSkill
- paper-plotSkill
- paper-reviewSkill
- paper-writingSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- could be automatic: a setting could enforce it
- Distinctive: line 37
Do not merge stale results left by failed invocations.
- Distinctive: line 40
Verify title, available authors and abstract against source API/primary source.
- Very specific: line 68
Run verify-results.py on the knowledge subtree and retain its output.
- Distinctive: line 76
Do not claim a complete systematic review, exhaustive search, or passed R3 until its required source, extraction and bibliography checks …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Systematic Research
Retrieve real sources, preserve provenance, and apply paper-extract to accessible
material. Never generate catalog metadata or paper claims from memory.
flowchart TD
A[Discover engines and read help] --> B[Search independent available engines]
B --> C{Request succeeded?}
C -->|No| D[Diagnose dependencies, network, rate limit or query]
D --> E[Retry boundedly or use callable search/browser tool]
E --> F[Preserve actual tool outputs and primary evidence]
C -->|Yes| F
F --> G[Merge/dedup without changing raw outputs]
G --> H[Verify identity against source API or primary source]
H --> I{Identity established?}
I -->|No| J[Flag affected item; continue verified items]
I -->|Yes| K[Download/save accessible source]
K --> L[paper-extract, bibliography, R3 verification]R0: Retrieval and identity
- List
scripts/search-*.pyandsearch-engines/; read matching engines' help. Pair domain and general engines where available. Do not send a free-text topic to a conference-listing engine. Use separate output directories for each run. - Install optional dependencies only when needed. Read retrieval-and-failures for setup, USENIX syntax, output contracts, retries and callable-tool fallback.
- Inspect exit status. Failure is not zero hits. Nonzero invocations write
search-error.json; successful invocations includestatus: successand count. Do not merge stale results left by failed invocations. - Preserve raw script/tool outputs. Merge and dedup by URL/DOI without inventing entries or fields. Each field must trace to a retrieved response.
- Verify title, available authors and abstract against source API/primary source. Compare up to the first three authors, allowing fewer-author papers. Preserve the response, method and discrepancies. API failures are not matches.
- The bundled verifier supports arXiv only. Run it on a COPY, retaining raw input. DOI/OpenAlex/web items use saved source responses and verification records; never send unrelated identifiers to the arXiv API.
- Download or save actual PDF/HTML content before extraction. A search snippet cannot support design or evaluation claims. Flag abstracts-only access.
<HARD-GATE-IDENTITY>
Unresolved identity mismatches block the affected item. Continue independently
verified items; report unavailable sources and incomplete coverage. Never
fabricate missing metadata or source files to satisfy a gate.
</HARD-GATE-IDENTITY>E: Source extraction
Discover the sibling paper-extract skill and recursively list its templates and
references. Read its SKILL.md; follow E0, E1, E1.5 and E2 as requested. Do not
assume a template path. Record claims with actual sections/pages and distinguish
source claims from proposed designs or hypotheses.
Each knowledge item contains actual source material, tldr.md, l0.md, l1.md
when required, and bibentry.bib. Use bibtexparser; citation metadata must trace
to retrieval/verification evidence. Aggregate with collect-bib.py as needed.
R3: Completion
Run verify-results.py on the knowledge subtree and retain its output. Check
source existence, required extraction files, citation URL/DOI and author identity.
Spot-check 2–3 decompositions against their sources for system names, claims and
section evidence. Correct errors before declaring the library complete.
<HARD-GATE-COMPLETE>
Exploratory discussion may proceed from accessible primary evidence while the
library is incomplete. Label facts, inferences, proposals and untested goals.
Do not claim a complete systematic review, exhaustive search, or passed R3 until
its required source, extraction and bibliography checks actually pass.
</HARD-GATE-COMPLETE>Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

