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.
git clone --depth 1 https://github.com/BanibrataChatterjee/AwesomeSalesforceSkillsWrote 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/commands/banibratachatterjee/awesomesalesforceskills/preflight-load)<a href="https://agentmods.dev/commands/banibratachatterjee/awesomesalesforceskills/preflight-load"><img src="https://agentmods.dev/badge/commands/banibratachatterjee/awesomesalesforceskills/preflight-load/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/banibratachatterjee/awesomesalesforceskills/preflight-load"><img src="https://agentmods.dev/badge/commands/banibratachatterjee/awesomesalesforceskills/preflight-load.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00000 | $0.00551 |
| Opus 5 | $0.00000 | $0.00275 |
| Sonnet 5 | $0.00000 | $0.00110 |
| Haiku 4.5 | $0.00000 | $0.00055 |
Grade A, and why
preflight-load 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 10d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/preflight-load — Go/no-go checklist for a planned data load
Wraps agents/data-loader-pre-flight/AGENT.md. Audits the object's active automation, VR bypass state, duplicate rules, required fields, sharing recalc cost, storage quota, and recommends the loader + exact CLI command.
Step 1 — Collect inputs
Ask the user:
1. Object API name?
Example: Account
2. Operation? insert / upsert / update / delete / hard-delete
3. Row count (integer)?
Example: 800000
4. Target org alias (required — every check is live-org)?
5. Source description (plain English)?
Example: "NetSuite customer export, one row per account, external-id = netsuite_customer_id__c"
6. External ID field (required for upsert)?
7. Window (optional — business-hours boundary)?
Example: "this Saturday 2am-6am PT"
If the operation is hard-delete, require the user to confirm the specific compliance driver.
Step 2 — Load the agent
Read agents/data-loader-pre-flight/AGENT.md + mandatory reads.
Step 3 — Execute the plan
- Probe the object's active automation stack (flows, triggers, VRs, processes)
- Check each automation for bulk-safety at the target volume
- Check duplicate rule interactions + policy
- Check record type defaults for the loader user
- Check required-field coverage vs source mapping
- Check sharing recalc cost + data skew
- Check storage quota impact
- Pick the loader + emit the exact CLI command
- Rollback plan
Step 4 — Deliver the output
- Summary: go/no-go + confidence
- Findings table (P0 → P1 → P2)
- Loader recommendation (CLI + batch size + concurrency)
- Pre-load checklist
- Post-load checklist
- Rollback plan
- Process Observations
- Citations
Step 5 — Recommend follow-ups
/audit-validation-rulesif VR bypass gaps surfaced/design-duplicate-ruleif dup-rule blocks surfaced/architect-permsif the integration user's PSG needs work/detect-driftpost-load for verification
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.
- 10d ago First seen · 83 lines · 0 tokens per session scan A 1baf233e038d
preflight-load is a command published in the GitHub repository BanibrataChatterjee/AwesomeSalesforceSkills (3 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 551 tokens. 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.