related-work-writing
Skill15 starsChanged 10 days agoMITView on GitHub
Use when writing or auditing the Related Work section. Organises prior work by axis rather than chronology, builds the asymptotic comparison table with an "Ours" row, writes the bridge and "Our work" paragraphs, and checks every characterisation of prior work against its source.
4 other projects use a version of this.
Adopted by
Most recently taken up by
- willlee1995/skillstheir own version, first seen Oct 13, 2026
- dongzhigang13305312738-art/paper-skillstheir own version, first seen Jul 21, 2026
- sergeeey/Claude-cod-top-2026their own version, first seen May 13, 2026
- lingzhi227/agent-research-skillstheir own version, first seen Feb 20, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- lingzhi227/agent-research-skills★ 350same name
- sergeeey/Claude-cod-top-2026★ 9same name
- dongzhigang13305312738-art/paper-skills★ 1same name
- willlee1995/skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository29 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- abstract-craftSkill
- anonymize-checkSkill
- artifact-packSkill
- baseline-pinSkill
- bench-protocolSkill
- bib-verifySkill
- camera-readySkill
- eprint-searchSkill
- experiments-writingSkill
- falsifySkill
- figure-harvestSkill
- idea-mining-loopSkill
- lean-bridgeSkill
- lit-matrixSkill
- log-to-evidenceSkill
- mock-reviewSkill
- paper-figuresSkill
- paper-playbookSkill
- param-estimationSkill
- phase-gateSkill
- polish-writingSkill
- reading-notesSkill
- rebuttalSkill
- sage-checkSkill
- technique-overviewSkill
- textbook-indexSkill
- venue-calibrationSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 4 edited versions we read keep these.
1
Distinctive
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
- Very specific: line 21
Verify each cost formula against the original (page/section noted in LITERATURE.md).
- Distinctive: line 30
Tone filter: remove "unfortunately", "fail", "naive", "suffer", "only".
“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Related-work writing
Inputs
LITERATURE.md (related-work matrix from lit-scout), refs.bib (verified), the
objective equation and framework from the introduction/overview.
Procedure
- Choose axes. From the literature matrix pick one or two axes along which all relevant works improve (what they reduce, what structure they exploit). Write them as a pair of contrasting verbs if possible ("restricts where" / "restricts how"; "fewer rounds" / "fewer bytes").
- Place each work. For each work record: axis, method in one line, cost formula
in its own notation translated to ours, scope restrictions (†/‡), venue'year.
Verify each cost formula against the original (page/section noted in
LITERATURE.md). Where later papers paraphrase an earlier paper's bottleneck, compare with the earlier paper's own experiments section. - Build the table (
templates/paper/sections/related_table.texstyle): grouped rows, last row\textbf{Ours}, caption defines all symbols. - Write the paragraphs: lead-in (3 sentences) → classic works on axis 1 (one
sentence each, shared limitation last) → recent works (two contrasting bullets) →
bridge (
\textbf{Insight from ...}) →\textbf{Our work.}(five sentences) → complementary approaches → concurrent work. - Tone filter: remove "unfortunately", "fail", "naive", "suffer", "only"; replace with factual scope statements ("... assumes ... rather than showing ...", "... instantiates a single case, leaving open ...").
- Self-citation check: own prior work in third person, critiqued like others.
- Coverage check with
lit-scout: the last 12–18 months of ePrint for the topic keywords; any close concurrent work gets a labelled paragraph. - Bib hygiene: published versions over preprints when they exist; ePrint entries
with the exact author list of the ePrint page; braces around acronyms in titles for
splncs04. (Bib verification itself is owned bylit-scout.)
Placement in the paper
- IACR LNCS: usually §1.1 inside the introduction.
- Design papers: a "State of the art" subsection in the constraints/design section, one paragraph per competitor: who → technical core → its trade-off; last sentence points to the performance comparison section.
- Security conferences: often a separate section near the end; keep a short positioning paragraph in the introduction anyway.
Anti-patterns
- A chronological list of summaries without a thesis.
- Characterising a prior work by a number from a secondary source.
- A table whose "Ours" row differs from the abstract formula.
- Omitting the strongest baseline because it is inconvenient (reviewers will name it).
Output
paper/sections/related.tex, table in the same file or related_table.tex,
verification notes appended to LITERATURE.md.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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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.

