SKILLEMALL.ai

BC memory-compress

Never let your agent forget what matters. Compress verbose daily logs into structured summaries — 4-8x compression, zero information loss. Inspired by classical Chinese writing: strip redundancy, keep turning points, let structure carry meaning. Smart hybrid extraction finds key events, lessons, decisions and todos from any markdown format. No API keys, no vector DB, no dependencies. Just run it. Works with any OpenClaw agent, Cursor, Claude Code, or any markdown-based memory system.

ClawHub Agent Skills author: 翎麟 v1.2.1 MIT-0 3 files body ≈ 1 183 tokens Open the sourceclawhub.ai analyzed 2 d ago

Never let your agent forget what matters.

As a process C 64/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

IntegrationAI and agentsLearningtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
C
64/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • 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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 64/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 100Tools and files. No external tools needed
  • 100Steps. 8 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1183 tokens

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
  • +4Description does not say when NOT to use the skill (false activations)
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 488: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 8 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)

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

External checks

ClawHub: suspicious
This local memory-compression skill is purpose-aligned, but it needs review because it can carry untrusted log text into long-term agent memory and uses an unsafe default temporary output path.
LLM: suspicious (high) · VirusTotal: · 12 Sept 2026