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sapien47

sap-pam

by sapien47

Check a system landscape

pam_check_landscape

Check SAP systems from a free-text list against PAM to match product versions, rate maintenance support risk, and identify upgrade options.

Instructions

Check a list of SAP systems/components (free text, e.g. from a design document or system list) against PAM. Matches each to a product version, rates support risk (critical, high, medium, low or unknown) and gives upgrade options (newer version of the same product, announced versions, SAP's strategic successor). Fuzzy matches should be confirmed by a person.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
systemsYesSystem or product names, e.g. ['ECC 6.0 EHP8', 'SAP NetWeaver 7.4', 'BW/4HANA 2021']
warnMonthsNoFlag as medium risk if mainstream maintenance ends within this many months (default 12)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does reasonably well: it discloses the output content (version match, risk tier, upgrade suggestions) and the exact risk taxonomy (critical/high/medium/low/unknown). It leaves the read-only nature, the 200-item batch ceiling, and any rate/latency behavior to the schema rather than stating them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three dense sentences with zero filler: purpose, then the three outputs, then the one caution. The most decision-relevant information (what it checks and against what) is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations and no output schema, the description does the necessary work by enumerating the three return categories and the risk vocabulary. It stops short of covering batch limits, partial-failure behavior, or what a fuzzy vs. exact match looks like in the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning: it clarifies that 'systems' accepts free-text design-document entries and that matching is fuzzy, and its mention of the 'medium' tier implicitly explains what warnMonths controls. It does not, however, restate the default of 12 or the 1-60 bounds.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (check) and resource (a list of SAP systems/components against PAM) plus the enrichment it returns: product version match, support-risk rating, and upgrade options. An agent can tell this is the batch/landscape-ingestion counterpart to pam_get_product or pam_upgrade_options, but the description never names a sibling to make the boundary explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It names the input scenario clearly ('free text, e.g. from a design document or system list'), which tells the agent when this tool fits. It also adds a workflow caveat ('Fuzzy matches should be confirmed by a person'), but gives no explicit when-not condition or pointer to the single-product siblings for follow-up.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.