Agent Output Formats

Agent Output Formats

Core principle — convert, don't regenerate

Every runtime agent produces a canonical pair: markdown + JSON envelope. That pair IS the source of truth. When a consumer asks for Excel/PDF/etc., the correct answer is to convert from that pair, not to re-run the agent with different instructions.

Reasons:

1. Reproducibility — the canonical deliverable is checked into docs/reports/. Six months later, anyone can regenerate the Excel from it. If the consuming AI regenerates by re-asking the agent, the output may differ due to LLM stochasticity.
2. Auditability — the run_id in the envelope is the tracking key. The Excel/PDF should reference it in its header, so "which run produced this?" is always answerable.
3. Minimal dependencies — reinstalling exceljs, xlsxwriter, weasyprint, etc. into a consumer's project every time someone wants a different format bloats their project's dependency tree.

Conversion decision tree

START: Consumer wants deliverable in format X.

Q1. Is X markdown or JSON?
    → Already the canonical form. No conversion needed; hand them the file path.

Q2. Is X a format the consumer's existing tooling handles natively?
    ├── Slack message / email body → paste the TL;DR + envelope-link from the markdown
    ├── Confluence / Notion / Obsidian → import the markdown directly (all support markdown import)
    ├── Jira / ServiceNow ticket → paste TL;DR in description + link the report file
    └── GitHub issue → embed markdown inline; link the report path
    → Prefer this path. Zero new dependencies.

Q3. Does the consumer want a "table" from the markdown?
    ├── CSV: extract markdown tables using `pandoc` (most dev machines have it)
    ├── Excel from the JSON envelope: use `jq` + `csv2xlsx` CLI tools (lighter than a full SDK)
    └── If neither pandoc nor jq: recommend installing pandoc (1 tool, system-level, widely used)

Q4. Does the consumer want PDF?
    → `pandoc .md -o .pdf` — single command, no new project deps
    → If pandoc isn't available: recommend a system-wide install, NOT a project-level dep

Q5. Does the consumer want something format-specific (e.g. ServiceNow change ticket)?
    → Extract the fields from the JSON envelope (it's keyed for exactly this)
    → Template into the target system via its normal integration path
    → Do NOT ask the agent to regenerate in the target format

Recommended Workflow

1. Confirm the canonical deliverable exists — docs/reports//.{md,json}. If not, run the agent first.
2. Check the consumer's tooling — do they already have pandoc, jq, csv2xlsx? The answer is almost always yes for #2 and often for #1.
3. Walk the decision tree above.
4. Produce the conversion command — a one-liner the user runs in their shell, not code added to their project.
5. Include the canonical run_id in the converted artifact's header — so auditors can trace it back.
6. Record the conversion path in the team's docs — next person who asks has a precedent.

Key patterns

Pattern 1 — Markdown → PDF via pandoc

pandoc docs/reports/user-access-diff/2026-04-17T21-14-05Z.md \
    -o ~/Desktop/user-access-diff.pdf \
    --metadata title="User Access Diff — Christina vs Carrie" \
    --metadata date="2026-04-17"

Zero project dependencies added. Works because pandoc is a widely-available system tool.

Pattern 2 — JSON envelope → Excel via jq + csv2xlsx

# Extract the findings array from the envelope as CSV.
jq -r '.findings | (map(keys) | add | unique) as $keys |
       ($keys | @csv), (.[] | [.[$keys[]]] | @csv)' \
    docs/reports/user-access-diff/2026-04-17T21-14-05Z.json \
    > /tmp/findings.csv

# Convert to xlsx.
csv2xlsx /tmp/findings.csv /tmp/findings.xlsx

Or, if the user has Excel open:

open /tmp/findings.csv          # macOS; Excel imports CSV natively

Pattern 3 — Envelope → ServiceNow change request

Extract the fields ServiceNow needs from the envelope:

jq '{
    short_description: .summary,
    description: .summary + "\n\nRun ID: " + .run_id +
                 "\nConfidence: " + .confidence +
                 "\nFull report: " + .report_path,
    priority: (if .findings | map(.severity) | any(. == "P0") then "1"
               elif .findings | map(.severity) | any(. == "P1") then "2"
               else "3" end)
}' docs/reports//.json

Paste the JSON into the ServiceNow integration payload. No project deps.

Pattern 4 — Notion / Obsidian / Confluence import

All three accept markdown imports directly. The user uploads the .md file via the platform's UI.

Preservation tip: include the run_id as a frontmatter field at the top of the markdown report, so when the page is imported, the run_id survives as a property.

Pattern 5 — When conversion requires a heavy dependency

Scenario: user wants interactive Excel with embedded formulas referencing cells.

• Don't install exceljs / openpyxl into their project.
• Recommend they open the CSV in Excel and author the formulas there — the CSV round-trips fine.
• If they insist on scripted generation, recommend a one-off Python script in ~/bin/ or a dedicated report-tool project — NOT the project where the agent was invoked.

Bulk safety

When converting reports for multiple runs in a batch:

• Use find docs/reports// -name '*.md' -exec pandoc ... to iterate, not one-by-one invocations.
• If converting to a centralized destination (e.g. uploading 50 reports to Notion), respect API rate limits.
• Never batch-convert and delete the canonical markdown — always retain the source.

Error handling

• Canonical deliverable missing → refuse to convert. Run the agent first.
• Conversion tool missing → recommend system-wide install, not project-local.
• Target format can't represent a field from the envelope (e.g. nested arrays in Excel) → flatten in the CSV step, not by regenerating.

Well-Architected mapping

• Operational Excellence — standardized conversion paths reduce "how do I turn this into Excel?" support tickets.
• Reliability — conversion-not-regeneration preserves the canonical run_id as the auditable thread.

Anti-patterns

1. Re-asking the agent to regenerate in the new format. The agent is an expensive LLM call. Conversion is a cheap shell command. Always convert from the canonical.

1. Installing format-specific libraries into the user's project. exceljs, xlsxwriter, weasyprint — these are conversion tools, not project dependencies. Install system-wide or run from a dedicated CLI project.

1. Stripping the run_id. The converted artifact must reference it somewhere (header, filename, metadata). Without it, nobody can trace which run the Excel came from.

1. Opening up new output-format surfaces on the agent itself. If someone asks for "JIRA native format" as an agent output, refuse. The agent outputs canonical markdown+JSON. JIRA conversion is downstream.

Official Sources Used

• Salesforce Architects — Reporting & Analytics Patterns: https://architect.salesforce.com/
• Pandoc Documentation (third-party CLI): https://pandoc.org/MANUAL.html
• Salesforce Developer — REST API: https://developer.salesforce.com/docs/atlas.en-us.apirest.meta/apirest/introwhatisrestapi.htm
• Salesforce Help — External Services: https://help.salesforce.com/s/articleView?id=sf.external_services.htm

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: PranavNagrecha
• Source: PranavNagrecha/AwesomeSalesforceSkills
• License: Apache-2.0
• Homepage: https://pypi.org/project/sfskills-mcp/

Install and usage instructions live in the source repository linked above.