SKILLEMALL.ai

BC unified-session

Unify all chat channels into one shared AI session for seamless cross-device continuity. Start a conversation on your laptop, continue from your phone — same context, same memory, zero loss. Use this skill whenever: - User wants multiple messaging channels (DingTalk, Feishu/Lark, Telegram, Discord, WhatsApp, Signal, Slack, webchat) to share one conversation - User mentions "shared session", "cross-device", "multi-channel", "unified session", "continue conversation", "seamless", "context lost", "memory lost", "上下文丢失", "记忆丢失", "多端共享" - User says their bot "forgets" what was said when they switch from one app to another - User asks how to make Telegram/Discord/DingTalk/Feishu/WhatsApp share context with webchat - User wants to switch between desktop and mobile without losing conversation history - User mentions dmScope, session routing, channel isolation, or session merging - User describes wanting to pick up where they left off on a different device or chat app - User complains about having separate conversations on each channel when they only have one agent - Even if the user doesn't use technical terms — if they describe the pain of "switching apps and the AI doesn't remember", this is the skill to use

ClawHub Agent Skills author: 1052326311 v1.3.0 MIT-0 3 files body ≈ 1 758 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorSlackDiscordTelegramWhatsAppInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1223 chars, limit 1024

Process rating: all ten parameters 63/100

  • 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. 4 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 21 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1758 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 17 top-level sections: this looks like several domains in one skill

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 1222: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -220 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 10 example trigger phrases
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (12 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.

External checks

ClawHub: clean
This instruction-only skill is purpose-aligned and disclosed, but users should only use it for a personal OpenClaw bot because it intentionally merges chat context across channels.
LLM: benign (high) · VirusTotal: · 29 May 2026