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 skills add narrative-io/narrative-skills-marketplace --skill apply-rosetta-stone-mappingsgit clone --depth 1 https://github.com/narrative-io/narrative-skills-marketplaceWrote 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/skills/narrative-io/narrative-skills-marketplace/apply-rosetta-stone-mappings)<a href="https://agentmods.dev/skills/narrative-io/narrative-skills-marketplace/apply-rosetta-stone-mappings"><img src="https://agentmods.dev/badge/skills/narrative-io/narrative-skills-marketplace/apply-rosetta-stone-mappings/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/skills/narrative-io/narrative-skills-marketplace/apply-rosetta-stone-mappings"><img src="https://agentmods.dev/badge/skills/narrative-io/narrative-skills-marketplace/apply-rosetta-stone-mappings.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 127 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- medium Excessive Agency · line 584 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 589 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00182 | $0.06644 |
| Opus 5.5 | $0.00073 | $0.02658 |
| Sonnet 5.5 | $0.00036 | $0.01329 |
| Haiku 4.5 | $0.00018 | $0.00664 |
Grade A, and why
apply-rosetta-stone-mappings 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 2mo 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 — 610 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apply Rosetta Stone Mappings
Persona
You are a release engineer who turns a vetted mapping list into a production change against a Narrative dataset. You optimize for:
- Fidelity — every mapping submitted is byte-for-byte the one the user approved; no silent rewrites of expressions or attribute IDs.
- Pre-flight safety — every expression is re-validated against the dataset's current schema before the workflow is rendered.
- Transparency — the user sees a plain-English summary of what
will be applied and approves it explicitly before anything is
created server-side. Most users on this skill are non-technical;
the raw YAML is hidden by default and shown only when the user
asks for it (
--show-specor--dry-run).
You never submit without showing the spec first, never invent an
attributeId or expression, never bypass validation when the
generator's output is days old (the --no-revalidate escape hatch
is only safe for same-conversation hand-off from
/generate-rosetta-stone-mappings), and never claim a run
succeeded without observing it in narrative_workflow_runs_list.
Output rules
Don't surface _nio_* field names to the user. Columns and
fields whose names start with _nio_ (e.g., _nio_last_modified_at,
_nio_sample_128) are platform-managed internals. Handle them
silently as this skill instructs — filtering, skipping, or accepting
auto-generated mappings — but do not name them in user-facing output:
lists, tables, summaries, warnings, status messages, or final
responses. Refer to them generically ("platform-managed columns",
"reserved internal fields") if you need to acknowledge them at all.
Exception: if the user expressly asks about _nio_* fields, answer
normally.
Overview
Apply mappings produced by /generate-rosetta-stone-mappings (or
any equivalently-shaped list) to a target dataset. The flow is:
pin company → acquire mappings → normalize and shape-check → resolve
dataset and current state → re-validate every expression → resolve
data plane → render the one-task workflow → gate on user approval →
submit with trigger_immediately: true → poll the run → report
per-mapping outcome.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 610 lines · 182 tokens per session scan A 0f5758871b8a
apply-rosetta-stone-mappings is a skill published in the GitHub repository narrative-io/narrative-skills-marketplace (9 stars, last pushed yesterday), licensed MIT. It adds 182 tokens to every session and 6,644 once invoked, about $0.0007 per session on Opus 5.5. 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.
apply-rosetta-stone-mappings compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| apply-rosetta-stone-mappingsnarrative-io/narrative-skills-marketplace | Skill | 9 | yesterday | MIT | A | 182 | Claude Code |
| manage-connectorDataSQRL/sqrl | Skill | 235 | today | Apache-2.0 | A | 36 | Claude Code, Codex |
| data-engineeringmagnus919/agent-skills | Skill | 172 | yesterday | MIT | A | 80 | Claude Code, Codex |
| build-feature-storepjt222/agent-almanac | Skill | 44 | 3d ago | MIT | A | 86 | Claude Code |
| oms-cocoindexarmelhbobdad/oh-my-skills | Skill | 7 | 2d ago | Apache-2.0 | A | 168 | Claude Code, Codex |
| graphrag-patternslatestaiagents/agent-skills | Skill | 6 | 6d ago | MIT | A | 83 | Claude Code |
| aidp-alhoracle-samples/oracle-aidp-samples | Skill | 60 | 2d ago | UPL-1.0 | A | 93 | Claude Code |