Scan ICE-Crawler extraction logs, pick promising algorithms/tools, and emit skill creation proposals (name, scope, source files, next steps).
SkillScore77Maintained
Automatic
◆Doc Ops pack
Last verified 8/6/2026
What it changes
Passed 14 of 18 test cases with the skill, and 6 of 18 without it.
Without skill32%
With skill77%
Checks it passed that the model alone missed
Uses summary_path as the key name
Uses ts for the ISO timestamp field name
Uses next_actions as the array field name
and 11 more in the full report
10 fixed7 passed either way5 still failing0 broke
Pass-rate lift
+45 pp
Tokens
0%
Agent turns
0%
Response time
-47%
Model gemini-3.6-flashMeasured 8/6/2026v117 of 22 cases passed with skill · 18 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 9
Prompt
In the proposal spec JSON for config-loader, what schema key records the path to the human-readable summary document, and what is its standard relative path pattern?
What was checked, without and with the skill
Checked
Without skill
With skill
Uses summary_path as the key name
Missed
Passed
Sets the value pattern to extractions/config-loader/SUMMARY.md
Missed
Passed
case-13 · gemini-3.6-flash · 8/6/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md60 lines2 files
Extraction Proposer
Use this skill after ICE-Crawler runs to convert harvested fossils into concrete skill proposals. It expects the extraction registry under ../ice-crawler-harvester/extractions (relative to this skill folder) and writes proposal specs under proposals/.
Reference: references/registry-workflow.md
Prerequisites
ICE-Crawler run metadata appended to extractions/index.jsonl.
Per-repo notes in extractions/<repo-slug>/SUMMARY.md (preferred) with code pointers.
jq or Python available for filtering JSONL (optional but useful).
Workflow
Review registry
Open extractions/index.jsonl to find recent entries. Use jq or Python to filter by tags, repo, or notable files.
Inspect corresponding SUMMARY.md files for algorithm descriptions and code paths.