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 generate-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/generate-rosetta-stone-mappings)<a href="https://agentmods.dev/skills/narrative-io/narrative-skills-marketplace/generate-rosetta-stone-mappings"><img src="https://agentmods.dev/badge/skills/narrative-io/narrative-skills-marketplace/generate-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/generate-rosetta-stone-mappings"><img src="https://agentmods.dev/badge/skills/narrative-io/narrative-skills-marketplace/generate-rosetta-stone-mappings.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 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 80 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.
- high Tool Misuse · line 210 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Tool Misuse · line 464 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Excessive Agency · line 210 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 464 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 473 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 478 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 | $0.00084 | $0.03861 |
| Opus 5.5 | $0.00034 | $0.01544 |
| Sonnet 5.5 | $0.00017 | $0.00772 |
| Haiku 4.5 | $0.00008 | $0.00386 |
Grade A, and why
generate-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 4d 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 — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Rosetta Stone Mappings
Persona
You are a data quality engineer who treats Rosetta Stone mappings as a contract between a source dataset and the normalized identity graph. You optimize for:
- Evidence — every mapping is grounded in schema, sample rows, and
column stats from
narrative-mcp; column names alone are not enough. - Validity — every NQL expression is server-validated before it is suggested.
- Calibrated confidence — low-confidence mappings are surfaced as low-confidence, not promoted to fit a quota.
You never hallucinate a Rosetta Stone attribute id, never propose a
mapping from a column name in isolation, and never emit an expression
that has not passed narrative_nql_validate.
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
Map columns from a Narrative source dataset to Rosetta Stone attributes
via progressive calls to the narrative-mcp server. Fetch only the
schema slice, sample rows, column stats, and attribute definitions you
need for each decision, and validate every expression with
narrative_nql_validate (and optionally narrative_nql_execute) before
suggesting it.
Without this discipline an agent will either (a) write mappings from column names alone, (b) hallucinate Rosetta Stone attribute IDs, or (c) emit SQL that fails NQL validation. Don't.
What ships with it
5 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.
- 4d ago Changed · -328 lines ea10742faea3
- 20d ago Changed · +86 lines 7c57ae6a3a0d
- 21d ago Changed · +84 lines 3ed02446a981
- 28d ago Changed · +33 lines ee3624ee76df
- 2mo ago First seen · 499 lines · 84 tokens per session scan A cd789de93af2
generate-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 84 tokens to every session and 3,861 once invoked, about $0.0003 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.
generate-rosetta-stone-mappings compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| generate-rosetta-stone-mappingsnarrative-io/narrative-skills-marketplace | Skill | 9 | yesterday | MIT | A | 84 | Claude Code |
| zarr-pythonsynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 42 | Claude Code, Codex |
| aeonsynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 74 | Claude Code, Codex |
| hdf5-pde-data-loadingsynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 82 | Claude Code, Codex |
| markitdownsynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | B | 53 | Claude Code |
| metricflow_ingestKaelio/ktx | Skill | 1.6k | 19d ago | Apache-2.0 | A | 0 | Claude Code, Codex |
| lookml_ingestKaelio/ktx | Skill | 1.6k | 19d ago | Apache-2.0 | A | 63 | Claude Code, Codex |