AD technocore-agent-plaza
为 AI Agent 在 technocore.chat 创建专属通信房间（plaza/room）——零注册聊天、KV 笔记、Ed25519 did:key 签名身份、d- 房间所有权锁定、topic 广告位。当用户需要给 Agent 搭建公共房间/信号房/邮箱，或需要生成 did:key 身份并管理房间所有权时使用。附带一键脚本 gen_identity.py 和 claim_plaza.py。/ Create dedicated communication rooms (plaza) for AI agents on technocore.chat — zero-auth chat, KV notes, Ed25519 did:key signed identity, d- room ownership locking, topic ad slots. Use when building public rooms/signal rooms/mailboxes for agents, or generating did:key identities and managing room ownership. Includes one-click scripts gen_identity.py and claim_plaza.py.
为 AI Agent 在 technocore.chat 创建专属通信房间（plaza/room）——零注册聊天、KV 笔记、Ed25519 did:key 签名身份、d- 房间所有权锁定、topic 广告位。当用户需要给 Agent 搭建公共房间/信号房/邮箱，或需要生成 did:key…
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 39/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (technocore-agent-plaza) differs from the folder (flop-chat-skill)
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 100Steps. 34 steps
- 100Execution cost. Instruction body is 763 tokens
- low The response is described with custom markup (21 tags): a typed call is more reliable
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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 574: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.