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/design-object)<a href="https://agentmods.dev/commands/banibratachatterjee/awesomesalesforceskills/design-object"><img src="https://agentmods.dev/badge/commands/banibratachatterjee/awesomesalesforceskills/design-object/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/design-object"><img src="https://agentmods.dev/badge/commands/banibratachatterjee/awesomesalesforceskills/design-object.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 | $0.00544 |
| Opus 5 | $0.00000 | $0.00272 |
| Sonnet 5 | $0.00000 | $0.00109 |
| Haiku 4.5 | $0.00000 | $0.00054 |
Grade A, and why
design-object 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/design-object — Design a Setup-ready sObject from a business concept
Wraps agents/object-designer/AGENT.md. Produces a complete object spec + sfdx metadata scaffold + deployment order.
Step 1 — Collect inputs
Ask the user:
1. Business concept (one sentence describing what the object represents)?
Example: "Track maintenance contracts linked to Accounts, with a primary technician and warranty expiration"
2. Target org alias (required — agent probes for overlapping design)?
3. Expected row volume? small (<100k) / medium (100k-10M) / large (>10M)
(Default: medium)
4. Integration source (optional)?
If rows will be sourced from an external system, pass the system name.
Drives External ID + upsert recommendations.
5. Sensitivity? standard / pii / phi / pci
(Default: standard; affects encryption + access recommendations)
If the concept is under 8 words or lacks enough signal to infer 3+ fields, STOP and ask clarifying questions.
Step 2 — Load the agent
Read agents/object-designer/AGENT.md + all mandatory reads.
Step 3 — Execute the plan
Follow the 10-step plan exactly:
- Probe org for overlapping design
- Decide standard vs custom
- Generate API name + label per naming conventions
- Design the field set
- Decide record types (only if persona variance signaled)
- Design sharing posture via the sharing-selection decision tree
- Plan validation rules at object creation
- Plan indexes (LDV objects or integration sources)
- Emit the deployment order
- Emit the spec + scaffold
Step 4 — Deliver the output
Return the Output Contract:
- Summary + confidence
- Design spec
- Scaffold metadata (fenced XML blocks, one per file)
- Deployment order
- Process Observations
- Citations
Step 5 — Recommend follow-ups
Suggest (but do not auto-invoke):
/architect-permsto design the persona PSes for the new object/audit-validation-rulesafter initial VRs are deployed/design-duplicate-ruleif the object is human-identity data/build-flowfor any automation on the new object
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 · 81 lines · 0 tokens per session scan A ba23377f3ac0
design-object 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 544 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
init
Initialize configurations for Supabase local development.
database-setup
Use when a project needs to store data and has no database yet. Setting up Supabase, creating tables, writing queries, and connecting them to the frontend. Written for designers.
ingest
Manually add knowledge to the Weaviate store.
json.batch_delete
Delete multiple JSON documents or paths in one itemwise batch.
json.batch_get
Read multiple JSON values by document and path.
json.index.drop
Drop a JSON secondary index by name.