SKILLEMALL.ai

BD read-claude-code-history

Reads, searches and exports local Claude Code and Kimi CLI history without resuming work: timelines, verbatim user input, keyword or fuzzy recall, file recovery from transcripts, and which session ran a given command in a known time window. Use when the user asks what was said, wants a session ID or original context, needs proof of what a session contained, or needs past-session runtime evidence about commands, tool calls and hook runs — query this index instead of raw-scanning transcript files. Not for Codex (use read-codex-history); with no platform or several named, start at local-conversation-history.

daymade/claude-code-skills Claude Code author: daymade MIT 44 files · 34 scripts body ≈ 6 835 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Reads, searches and exports local Claude Code and Kimi CLI history without resuming work: timelines, verbatim user input, keyword or fuzzy recall, file…

As a process D 46/100 · Unfinished process — References files that are not bundled: scripts/**/*.py

IntegrationSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
D
46/100
Unfinished process
References files that are not bundled: scripts/**/*.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 28. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6835 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/**/*.py
  • note edit-residue the text marks something as outdated (lines 367, 374, 433): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 46/100

Will not run. References files that are not bundled: scripts/**/*.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/**/*.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 7 mutating operations with no state check
  • 60Failures and branches. 2 branches
  • 70Execution cost. Instruction body is 6835 tokens
  • 100Steps. 24 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The response is described with custom markup (17 tags): a typed call is more reliable
  • medium 6 test cases, all positive: not one "should refuse" or "should ask first"
  • low No test case covers injection arriving through data

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 612: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)
  • +3All 9 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.