Search and analyze your own session logs (older/parent conversations) using jq.
71
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 94%
↑ 1.91xAgent success when using this skill
Validation for skill structure
Cross-session text search
jq for parsing
0%
100%
rg for search
0%
100%
type=="message" filter
50%
80%
type=="text" content filter
100%
100%
role=="user" filter
100%
100%
rg case-insensitive
0%
100%
Correct session identified
100%
100%
User questions extracted
100%
100%
No toolCall/thinking noise
100%
100%
All sessions processed
100%
100%
Without context: $0.2271 · 48s · 14 turns · 19 in / 3,125 out tokens
With context: $0.5159 · 1m 37s · 30 turns · 191 in / 5,864 out tokens
Session cost analysis
jq for cost extraction
0%
100%
Correct cost field path
0%
100%
Null fallback // 0
0%
100%
jq -s slurp mode
0%
100%
Date from first line
70%
100%
Date extraction via cut
70%
100%
awk daily aggregation
50%
100%
Results sorted descending
0%
0%
Per-session totals
100%
100%
Correct total amounts
50%
100%
Without context: $0.2197 · 53s · 15 turns · 17 in / 3,899 out tokens
With context: $0.4503 · 1m 28s · 26 turns · 60 in / 5,696 out tokens
Tool call frequency analysis
jq for parsing
0%
100%
type=="toolCall" filter
0%
100%
.name extraction
0%
100%
type=="message" filter
0%
50%
sort | uniq -c ranking
100%
100%
Multi-session processing
100%
100%
Correct top tool
100%
100%
Correct tool counts
100%
100%
No non-tool content
100%
100%
Content iterated correctly
0%
100%
Without context: $0.2218 · 50s · 17 turns · 20 in / 3,387 out tokens
With context: $0.4409 · 1m 22s · 25 turns · 63 in / 4,791 out tokens
Table of Contents
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.