SKILLEMALL.ai

CD tool-discovery

Agent 工具数量变多、上下文被工具定义占满时使用——设计工具发现与渐进式披露机制、实现 discover_tools 元工具与两层语义路由、选择索引式/检索式/主动发现/Skills 方案、处理动态加载破坏 KV Cache 的问题、评估 token 成本与工具选择准确率时查阅。含渐进式加载五步流程、工具数量阈值与关键实验数据。

bojieli/ai-agent-book Agent Skills author: bojieli Apache-2.0 1 file body ≈ 1 050 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Agent 工具数量变多、上下文被工具定义占满时使用——设计工具发现与渐进式披露机制、实现 discovertools 元工具与两层语义路由、选择索引式/检索式/主动发现/Skills 方案、处理动态加载破坏 KV Cache 的问题、评估 token…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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: 1. 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 46/100

  • 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
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 36 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1050 tokens
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (3 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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 167: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 36 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.