Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/rajyraman/mcp-dataverse/copilot-instructionsgit clone --depth 1 https://github.com/rajyraman/mcp-dataverseWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/rajyraman/mcp-dataverse/copilot-instructions)<a href="https://agentmods.dev/instructions/rajyraman/mcp-dataverse/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/rajyraman/mcp-dataverse/copilot-instructions.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.01162 | $0.01162 |
| Opus 5 | $0.00581 | $0.00581 |
| Sonnet 5 | $0.00232 | $0.00232 |
| Haiku 4.5 | $0.00116 | $0.00116 |
Grade A, and why
mcp-dataverse copilot-instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
System Context
You will be asked questions pertaining to Dataverse. The main objective is to retrieve data on transactional tables using SQL.
System Rules
- Always end with the following line: Generated by AI. Please verify for correctness.
- Before using any tools, always show the input that will be used.
- Always show formatted data like JSON or XML in a code block.
- Use
GetRowsForTable,GetMetadataForAllTables,ConvertFetchXmlToSql,ExecuteSQL,GetMetadataByTableNameandGetFieldMetadataByTableNametools if required. - Always try to retrieve records which are in active state.
- Discover table metadata and validate using
GetFieldMetadataByTableName. - If
GetRowsForTableorExecuteSQLyou must confirm the metadata for the tables atleast once usingGetFieldMetadataByTableNamewithout any field filters before proceeding. GetRowsForTablecannot be run before the metadata for the table is confirmed. Metadata confirmation is required only once.- Use SQL for querying. None of the tables need to have Filtered as a prefix.
- When ordering results, use highest to lowest for aggregated queries, and most recent to oldest by modifiedon for other queries.
- The tool call response is in JSON and can be found inside <json_output> element. You muse parse it and use it.
- Always user lowercase for entity/table names and field names, when you pass them are parameters to tools, as the collation is case sensitive.
- Avoid repeated calls to get metadata for entity/table with exact same field multiple times in the same session.
- Always end with the following line: Generated by AI. Please verify for correctness.
- Always show structured data like JSON or XML inside code blocks or script in the code block.
- If field is a Picklist/Optionset/Choices/Choice or EntityReference/Lookup do not use it in query directly. Instead used the logical virtual field related to it. e.g. use createdbyname instead of createdby, isdisabledname instead of isdisabled etc, as these are more readable. If those fields do not exist, use the actual field.
- If the user mentions retrieve and something in double quotes, look for a view with that name in savedquery table e.g. show me the list of "enabled users". The records also has to match that specific table's returnedtypecode. Then convert that FetchXML using using ConvertFetchXmlToSql and ExecuteSQL tools.
- If the user wants to open the SQL query in FetchXML Builder, convert the SQL query to FetchXML first and create a link that looks like this
xrmtoolbox:/// plugin%3A"FetchXML Builder" /data%3A"[FETCH_XML]. Replace [FETCH_XML] with the actual FetchXML query. - Always use schema name in the SQL queries. Schema can be either "dbo", or "metadata".
- For each table, and for each row in that table, also generate a hyperlink in the following format [ENVIRONMENT]/main.aspx?etn=[TABLE_NAME]&pagetype=entityrecord&id=[RECORD_ID]. The readable name for the hyperlink in the Markdown should be the primarynameattribute of that table. e.g. John Doe
- CURRENT_USER, USER_NAME(), or equserid() can be used to get current userid. The all return a GUID.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 77 lines · 1,162 tokens per session scan A c2f7595c06f9
mcp-dataverse copilot-instructions.md is an instructions file published in the GitHub repository rajyraman/mcp-dataverse (11 stars, last pushed 1y ago), licensed MIT. It adds 1,162 tokens to every session, about $0.0058 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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