BD mcp-apps-host-dev
Use when developing or debugging the MCP Apps host layer in any agent application — rendering sandboxed iframe cards, bridging postMessage ↔ gateway ↔ MCP server, or fixing security/architectural issues in the card pipeline. Covers the full bridge architecture, security model, and common pitfalls. Includes Hermes Desktop as a reference implementation.
Use when developing or debugging the MCP Apps host layer in any agent application — rendering sandboxed iframe cards, bridging postMessage ↔ gateway ↔ MCP…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
- warning
body-longSKILL.md body ≈ 6147 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70Execution cost. Instruction body is 6147 tokens
- 100Steps. 70 steps
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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
- -5TODO / placeholder text left in the skill
- +2Single-language instructions
- +3Description length 353: enough signal without eating the budget
- +4Structure: 42 headings
- +3Step-by-step instructions: 70 items
- +4Has examples (20 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.