SEGoS-data

Data assets for SE-GoS: Self-Evolving Graph-of-Skills for Skill Library at Scale (paper: arXiv:2609.08228, code: PKUfudawei/SEGoS).

This dataset hosts only what SE-GoS itself produces or repackages for convenience. The GoS skill libraries and prebuilt workspaces it builds on are not redistributed here — scripts/download_data.sh fetches them from the upstream GoS dataset davidliuk/graph-of-skills-data (davidliuk, 2026-04).

Contents

Assets are grouped by the experiment they belong to, so a single experiment's inputs can be fetched without pulling the rest.

Path	Used by
tasks/skillsbench_tasks.tar.gz	every table — 87 SkillsBench dockerized coding tasks (1.0 GB unpacked)
coldstart/segos_coldstart_skills1000.json	every table — the static (round-0) substrate: 1,000 skills, 863 semantic edges
full87/graphs/segos_evolved_skills1000_round1.json	main table (the SE-GoS cell) and multi-round table round 1 — 1,118 edges: 863 semantic, 228 workflow, 27 avoid
full87/graphs/segos_evolved_skills1000_round2.json	multi-round table round 2 — 1,375 edges (previous chain, see below)
full87/graphs/segos_evolved_skills1000_round3.json	multi-round table round 3 — 1,502 edges (previous chain, see below)
heldout/graphs/segos_evolved_skills1000_heldout_train50.json	held-out table — evolved on the 50 training tasks only — 999 edges: 863 semantic, 127 workflow, 9 avoid
full87/evolution/segos_evolution_deltas.tar.gz	the L1/L2/L3 deltas for all eight full-87 cells, plus the parsed signals
heldout/evolution/segos_evolution_deltas.tar.gz	the L1/L2/L3 deltas behind the held-out graph
full87/traces/segos_traces_round*.tar.gz	per-trial job trees for the full-87 runs (round-0 train, rounds 1-3 evals)
heldout/traces/segos_traces_heldout_eval.tar.gz	per-trial job trees for the held-out run (37 eval tasks)

Each trace archive holds one directory per task attempt with result.json, config.json, and the agent transcript.

The tarballs contain one top-level directory; extract with tar -xzf <archive> --strip-components=1. The graph JSONs and the deltas archive are what download_data.sh unpacks for you.

Regeneration status (2026-09-15)

round1 and heldout_train50 were regenerated from the static training traces with the avoid relation enabled at its default evidence bar, plus the non-contradiction invariant. Only their edge sets and weights changed; the three description rewrites in each were carried over, because the node update calls an LLM and is not reproducible offline.

• round 1: 1,102 → 1,118 edges (the workflow set also shifted from 239 to 228 because eleven trials of the training job were re-run after the original deltas were computed)
• held-out: 990 → 999 edges

The reward, token and runtime columns of the paper were measured on the previous graphs and have not been re-measured; a full re-run is pending.

round2 and round3 are deliberately left as they were. Their evolution consumes the round-1 evaluation traces, which were produced on the previous round-1 graph, so they cannot be regenerated until that re-run happens. Their deltas inside full87/evolution/segos_evolution_deltas.tar.gz are the previous chain's, unchanged; everything else in that archive is current.

The cold-start graph

SE-GoS does not start from GoS's LLM-validated typed graph. It starts from a deterministic semantic-only graph: every skill linked to its top-1 neighbour by signature-token overlap, no LLM pass and no embedding service.

coldstart/segos_coldstart_skills1000.json is exactly that substrate — the graph behind the static (round-0) row of every table in the paper (1,000 nodes / 863 edges). It is reproducible from the upstream GoS workspace in one command:

cd evaluation/skillsbench
PYTHONPATH=$PWD python -m evo.rebuild_graph \
  --igraph ../../data/gos_workspace/skills_1000_v1/graph_igraph_data.pklz \
  --edge-types sem --sem-metric token --semantic-k 1 \
  --out generated/shared/graphskills_bundle_semonly_token_k1_1000.json

--hnsw is not needed: the token metric reads node attributes from the official igraph pickle, so no embedding index or API key is involved.

The evolved graphs

The multi-round and held-out tables run on graphs that SE-GoS produced from execution traces, not on the cold start:

• full87/graphs/segos_evolved_skills1000_round{1,2,3}.json — the full-87 protocol, one L1/L2/L3 pass per round. Round 1 is the SE-GoS cell of the main table (1,102 edges); rounds 2 and 3 re-evolve and re-measure all 87 tasks.
• heldout/graphs/segos_evolved_skills1000_heldout_train50.json — evolved on the 50 training tasks of the disjoint 50/37 split only (990 edges), then measured on the 37 held-out tasks. A different artifact from round 1 despite the similar name; the two are never interchangeable.

full87/evolution/segos_evolution_deltas.tar.gz carries the L1/L2/L3 deltas and the parsed signals the graphs were built from, so the evolution itself can be recomputed offline (no agent runs). */traces/*.tar.gz carries the raw per-trial job trees if you want to replay the runs.

Usage

git clone https://github.com/PKUfudawei/SEGoS.git && cd SEGoS
./scripts/download_data.sh              # everything except traces
./scripts/download_data.sh --tasks      # SkillsBench tasks only
./scripts/download_data.sh --coldstart  # cold-start graph only
./scripts/download_data.sh --evolved    # evolved graphs + deltas (multi-round / held-out)
./scripts/download_data.sh --traces     # per-trial job trees for those runs (~1.2 GB)

Fetch one experiment's assets directly, without the rest of the dataset:

hf download PKUfudawei/SEGoS-data --include "heldout/*" --repo-type dataset
hf download PKUfudawei/SEGoS-data --include "full87/graphs/*" "coldstart/*" --repo-type dataset

GOS_HF_REPO overrides the upstream GoS dataset used for skill libraries and prebuilt workspaces; SEGOS_HF_REPO overrides this dataset.

Provenance

• SkillsBench tasks — from benchflow-ai/skillsbench. download_data.sh falls back to a sparse checkout of that repo if the archive here is unavailable.
• Cold-start graph — produced by this project from the upstream GoS workspace (see the rebuild_graph command above).
• Evolved graphs and deltas — produced by this project's evolution pass over traces from the SkillsBench runs. The graphs are the artifacts the tables are measured on; the deltas are the auditable record of what each update changed.
• Per-trial traces — the raw job trees those runs wrote: one directory per task attempt, holding result.json, config.json, and the agent transcript.
• Skill libraries / prebuilt workspaces — not hosted here; fetched from davidliuk/graph-of-skills-data. Note those *_v1 workspace archives hold undirected graphs from an earlier GoS cleanup implementation and reproduce older results only.