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BC foundry-iq

Foundry IQ knowledge bases. WHEN: make local or Blob documents searchable; create/diagnose KBs; triage unsupported connectors or multi-source KB creation/reconfiguration; connect existing KB to agents (including multi-source KBs); create/reuse a Search service; retrieve from an existing knowledge base with citations; no brand words needed. Read its procedure before query/target questions. NOT: other KB providers, repository-file search, classic Azure AI Search index/query/app work, generic agent creation.

microsoft/skills Agent Skills author: microsoft MIT 78 files body ≈ 723 tokens Open the sourcegithub.com↗ analyzed 20 h ago

Foundry IQ knowledge bases.

As a process C 51/100 · Has gaps — weak spots: steps, result and completion, when it triggers

ReferenceAzureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
96
Quality 40%
78
Run on models
none yet
Process rating
C
51/100
Has gaps
Steps w 15
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Secrets in code secret-high-entropy-token agents/connect-hosted.md:28
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      For omitted audience or `Unkn…sV2`, use the exact
      detector
    • low Secrets in code secret-password-literal references/bootstrap-azure.md:117
      Hard-coded password / key literal (may be an example)
      --headers api-key=phas…obe`. Never acquire a real key.
    • low Secrets in code secret-high-entropy-token references/platform-interfaces.md:49
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      `Unkn…sV2` for `AgenticIdentityToken`. For those schema
      quoted
    • low Concealment en-hide-from-user SKILL.md:40
      Instruction to hide actions from the user (negated — the text forbids it)
      Do not silently execute only the supported part of a compound request.
      negated

    Files scanned: 78. 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 51/100

    • 0Steps. Prose only: no discrete steps
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 100Tools and files. No external tools needed
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 723 tokens

    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)
    • +4Structure: 1 headings, hard to scan
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +2Single-language instructions
    • +3Description length 510: enough signal without eating the budget
    • +4Reference files are cited in the instructions (1 of 17)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.