BC bolta.skills.index
Bolta Skills Registry - canonical index and orchestration layer for all Bolta skills, organized by plane
As a process C 62/100 · Has gaps — weak spots: when it triggers, consistency, execution cost
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.
The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
medium Secrets in code
secret-labelled-tokenSKILL.md:385Labelled token / key literal (vendor format unknown — verify it is not a live credential)API Key: bolt…000
-
medium Secrets in code
secret-labelled-tokenSKILL.md:410Labelled token / key literal (vendor format unknown — verify it is not a live credential)API Key: bolt…000
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 17544 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "type" - note
frontmatter-keyunknown frontmatter key "roles_allowed" - note
frontmatter-keyunknown frontmatter key "agent_types" - note
frontmatter-keyunknown frontmatter key "tools_required" - note
frontmatter-keyunknown frontmatter key "inputs_schema" - note
frontmatter-keyunknown frontmatter key "outputs_schema" - note
frontmatter-keyunknown frontmatter key "organization"
Process rating: all ten parameters 62/100
- 0Progress reporting. Says nothing while it works
- 10Execution cost. Instruction body is 17544 tokens: crowds the task out of the window
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (bolta.skills.index) differs from the folder (bolta-skills-index)
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 261 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Running it twice. Mutating operations check current state
- 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 104: 120–800 characters recommended
- +1No license
- +2Single-language instructions
- +4Structure: 123 headings
- +3Step-by-step instructions: 261 items
- +3Output format is stated explicitly
- +4Has examples (33 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.