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 tuanductran/hr-skills --skill hr-talent-mappinggit clone --depth 1 https://github.com/tuanductran/hr-skillsWrote 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/tuanductran/hr-skills/hr-talent-mapping)<a href="https://agentmods.dev/skills/tuanductran/hr-skills/hr-talent-mapping"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-talent-mapping/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/tuanductran/hr-skills/hr-talent-mapping"><img src="https://agentmods.dev/badge/skills/tuanductran/hr-skills/hr-talent-mapping.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 | $0.00072 | $0.00727 |
| Opus 5 | $0.00036 | $0.00364 |
| Sonnet 5 | $0.00014 | $0.00145 |
| Haiku 4.5 | $0.00007 | $0.00073 |
Grade A, and why
hr-talent-mapping 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 5d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Talent mapping
Track named individuals — internal successors and external targets — against current and anticipated roles, so hiring and succession decisions can draw on a ready bench instead of starting a search from zero.
Supported tasks
- Building named-candidate maps for critical or hard-to-fill roles
- Cross-referencing internal succession candidates with external benchmarks
- Tracking external talent relationships over time (warm leads, past applicants, silver medalists)
- Mapping talent against anticipated future roles from workforce plans
- Identifying readiness gaps between mapped candidates and role requirements
- Prioritizing which mapped candidates to nurture actively vs. monitor passively
- Coordinating talent mapping with succession planning and 9-box reviews
- Building geography- or function-specific talent benches
- Refreshing talent maps as candidates change roles or companies
- Reporting bench strength and coverage gaps to leadership
- Feeding talent maps into proactive nurture and CRM campaigns
- Aligning talent mapping cadence with business planning cycles
Key prompts
Building talent maps
- "Build a named-candidate talent map for [role/function] with 3 internal and 5 external candidates, noting readiness and interest level for each."
- "Cross-reference our internal succession bench for [role] against external benchmarks to identify capability gaps."
- "What criteria should we use to decide whether a mapped candidate is 'ready now', 'ready in 1-2 years', or 'watch only'?"
- "Map talent against the roles in our [3-year] workforce plan for [function]."
Maintaining and prioritizing
- "Which mapped candidates for [role] should we actively nurture this quarter given upcoming openings?"
- "Design a cadence for refreshing talent maps so they don't go stale between planning cycles."
- "How do we track a 'silver medalist' candidate from a past search without it feeling transactional?"
- "Flag mapped candidates for [role] who may have changed companies or roles recently and need re-verification."
What ships with it
4 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.
- 5d ago First seen · 58 lines · 72 tokens per session scan A d918bddf3ee8
hr-talent-mapping is a skill published in the GitHub repository tuanductran/hr-skills (58 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 727 once invoked, about $0.0004 per session on Opus 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 2026-09-07.
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