SKILLEMALL.ai

BF sql-linker-cli

SQL-Linker CLI: Multi-DB CRUD (MySQL/PostgreSQL/SQLite) with bootstrap config generation, credential management (encrypted password via OS env + cloud dbpw_key), cloud audit sync to https://sqllinker.agentpower.hk.cn, and API key introspection. Per-invocation --approve flag for credential gate.

ClawHub Agent Skills author: CoderHanS v2.0.3 MIT-0 8 files body ≈ 6 246 tokens Open the sourceclawhub.ai analyzed 31 h ago

SQL-Linker CLI: Multi-DB CRUD (MySQL/PostgreSQL/SQLite) with bootstrap config generation, credential management (encrypted password via OS env + cloud…

As a process F 33/100 · Will not run — References files that are not bundled: scripts/service_layer/main.py

IntegrationMySQLPostgreSQLSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
100
Quality 40%
52
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: scripts/service_layer/main.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
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: 0. 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")
  • warning body-long SKILL.md body ≈ 6246 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/service_layer/main.py
  • note frontmatter-key unknown frontmatter key "requires"
  • note frontmatter-key unknown frontmatter key "permissions"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: scripts/service_layer/main.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/service_layer/main.py
  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 15 mutating operations with no state check
  • 70Execution cost. Instruction body is 6246 tokens
  • 100Steps. 38 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 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)
  • +3Output format is not stated: the model decides each time
  • -237 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 295: enough signal without eating the budget
  • +4Structure: 60 headings
  • +3Step-by-step instructions: 38 items
  • +4Has examples (22 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 52.

External checks

ClawHub: suspicious
This database skill is mostly disclosed, but its credential and SQL controls are inconsistent enough that users should review it before installing.
LLM: suspicious (high) · VirusTotal: · 27 Jun 2026