Notes from building the `skill-manager-router` skill — how to stop a large AI skill library from becoming chaos. Agar tumhare paas bhi 50+ skills hain, ye architecture rescue karega.


Problem


Hermes 100+ skills ho sakte hain. Ek task aata hai ("traffic drop?") aur 5 skills activate ho jati hain — sab apna analysis dete hain, conflict ho jata hai. Output confusing ho jata hai, aur agent galat skill ke conclusion pe action leta hai. More skills ≠ more intelligence. Zyada skills sirf zyada confusion laate hain agar unhe manage na kiya jaye.


Doctrine (6 rules)


1. **More skills do NOT automatically mean more intelligence.** Ek focused skill 10 generic skills se better hai.

2. **Har skill ka clear domain, trigger, exclusions hona chahiye.** Agar ye nahi hai, skill incomplete hai.

3. **One task = one primary skill.** Support max 2 ho sakte hain.

4. **Support skills tools hain, competing decision-makers nahi.**

5. **Duplicate skills merge ya deprecate karo.**

6. **Value-na-dikhaye skill default inactive raho.**


Mandatory metadata (har SKILL.md mei)



name, version, domain, purpose, triggers, exclusions,
inputs, outputs, primary_or_support, priority, dependencies,
conflicts_with, source_requirements, health_status,
usage_count, success_count, last_error

Ye 16 fields har skill ko self-describing banate hain. Bina iske, router decide nahi kar sakta kon sa skill kis task ke liye hai.


Router decision tree (10 steps)


1. Parse user/task intent.

2. Determine domain.

3. Retrieve candidate skills from registry.

4. Remove excluded/conflicting skills.

5. Rank by: specificity > health > recency > success history > dependency availability.

6. **Select exactly ONE PRIMARY.**

7. Add max TWO SUPPORT skills only if required.

8. Execute.

9. Validate output.

10. Record outcome (usage_count++, success/fail).


Step 6 sabse important hai — ek se zyada primary hone se conflict guaranteed hai.


Context budget guard



MAX_PRIMARY_SKILLS = 1
MAX_SUPPORT_SKILLS = 2
MAX_ACTIVE_SKILL_DOCS = 3
MAX_DUPLICATE_CAPABILITY = 1

Load: summary metadata first; full SKILL.md only for SELECTED skills. Isse context window bachaata hai aur speed badhti hai.


Conflict resolution


  • Specialized skill beats general skill.
  • Verified-healthy beats experimental.
  • First-party-data skill beats estimate-only for owned-site decisions.
  • Two skills cannot both issue final decisions on same subtask.
  • If conflict remains → record UNCERTAINTY, do NOT blend incompatible conclusions.

    • Last point critical hai: agent kabhi bhi do alag skills ke contradictory answers mix nahi karega. Wo uncertainty report karega.


    Real script I built


    `registry_scan.py` saare skills scan karta hai, metadata extract karta hai, `registry.json` mei dump karta hai. Multi-domain skills flag karta hai consolidation ke liye.


    `route.py ` task leta hai, registry se PRIMARY + SUPPORT suggest karta hai. Ranking function specificity (trigger words match), health (active=3, experimental=2), aur success_count count karta hai.


    Maine 15 skills scan kiye — multiple skills same domain mei mile (publishing, seo variants). Ye consolidate karne ke candidates hain.


    Example: SEO routing


    | Task | Primary | Support |

    ||||

    | Why did traffic drop? | gsc-intelligence | ga4-intelligence |

    | Why is this page slow? | technical-seo-guardian | none |

    | What article next? | content-opportunity-hunter | gsc-intelligence |

    | Write evidence article | citation-article-engine-v2 | content-opportunity-hunter |

    | Why not indexed? | indexing-sitemap-guardian | technical-seo-guardian |

    | Who cited us? | entity-citation-monitor | none |


    Consolidation rule


    Jab `conflicts_with` ya overlapping triggers mile:

  • Higher `health_status` + `success_count` wale ko PRIMARY rakho.
  • Doosre ko deprecate karo (`health_status: deprecated`, `absorbed_into` add karo).
  • Pinned skill ko bina owner approval delete mat karo.

    • Why this matters for autonomous agents


    Autonomous agent (jaise Hermes mesh) bina router ke random skills activate karega. Ek simple "article likho" task 5 skills trigger kar dega — seo-system, hindi-writer, publishing, governance, social. Router ensures: primary = seo-system, support = hindi-writer + social. Baaki exclude.


    My experience


    Pehle mere paas 11 skills the bina metadata. Task aata tha toh sab respond karte the. Ab `registry_scan` + `route.py` se exactly 1 primary milta hai. Output clarity 10x better hai, aur agent faster decide karta hai.


    FAQ


    **Q: Har skill mei 16 fields bharna zaroori hai?** Haan, at least name/domain/triggers/health_status. Baaki progressive fill karo.

    **Q: Duplicate kaise identify karu?** `registry_scan.py` multi-domain report deta hai. Manual bhi: triggers overlap dekho.

    **Q: Router khud skill hai ya system?** Dono — ek skill jo doosre skills ko route karta hai.


    Common mistakes


    1. **2 primary skills choose karna** — conflict guaranteed.

    2. **Metadata skip karna** — router blind ho jata hai.

    3. **Deprecated skills delete kar dena** — pinned hone par nuksan. Inactive rakho.

    4. **Context budget ignore karna** — saare SKILL.md load karo toh context bharta hai.


    *Infra note. Not trading/investment advice.*


    Deep dive: ranking function kaise kaam karti hai


    Router har candidate skill ko score karta hai. Formula simplified:


    
score = (trigger_matches × 2)
      + (health_rank × 2)
      + (success_count × 0.01)
      + recency_bonus

    `trigger_matches`: task description mei jo words skill ke triggers/domain me hain, unka count. "traffic drop" task mei agar skill ke triggers mei "traffic", "ranking", "gsc" hain aur task mei "traffic" hai, +2.


    `health_rank`: active=3, verified=3, experimental=2, inactive=1, deprecated=0.


    `success_count`: historical wins. Zyada weight nahi (0.01) taaki new skill bhi chance paye.


    Final: top scorer = PRIMARY. Agle 2 (score > 1) = SUPPORT.


    Registry.json structure (real)


    
{
  "gsc-intelligence": {
    "domain": "seo/gsc",
    "triggers": "traffic drop, ranking, query performance, ctr",
    "health_status": "active",
    "source_requirements": "GSC_OAUTH_TOKEN",
    "success_count": 12
  },
  "citation-article-engine-v2": {
    "domain": "content/creation",
    "triggers": "write article, draft, evidence",
    "health_status": "active",
    "success_count": 30
  }
}

    Is JSON ko `route.py` read karta hai. Har task pe rebuild nahi, sirf `registry_scan.py` jab skills change hon.


    Scenario: "NIFTY article likho with SEO"


    Bina router: seo-system + hindi-writer + publishing + social + nse-options-mcp sab trigger ho jayenge.

    Router ke saath:

  • Domain = "content creation + seo"
  • `citation-article-engine-v2` (triggers: write article) → PRIMARY score highest
  • `seo-system` (triggers: seo, on-page) → SUPPORT
  • `hindi-writer` (only if lang=hi requested) → SUPPORT or excluded

    • Result: 1 primary + max 2 support. Clean.


    Scaling to 100+ skills


    Jab 100 skills ho jayengi:

  • `MAX_ACTIVE_SKILL_DOCS = 3` ensure karta hai ki context window mei sirf 3 full SKILL.md load hon.
  • Baaki sirf metadata se match karo.
  • `conflicts_with` graph se circular dependencies detect karo.

    • Ye hi difference hai working agent aur chaotic agent mei.


    Kyun maine ye banaya


    Mera mesh 3 nodes pe chalta hai (Mac + 2 phones). Har node alag skills chala raha tha. Ek task "publish karo" pe Mac pe 5 skills activate ho rahe the, phones pe alag. Inconsistency thi. Router ne standardize kiya — har node same routing logic use karta hai.


    Migration guide (apne skills par lagao)


    1. Har SKILL.md ke frontmatter mei 16 fields add karo.

    2. `registry_scan.py` run karo → registry.json banega.

    3. Har task pe `route.py` call karo pehle.

    4. Conflicts resolve karo (merge duplicates).

    5. Health status update karo har week.


    2 ghante ka kaam, lifetime ki clarity.


    *Infra note. Not trading/investment advice.*





    More From Shakti Tiwari


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  • 🏛️ **Entity:** [Wikidata Q140689249](https://www.wikidata.org/wiki/Q140689249)

    • Real implementation notes


    Maine `registry_scan.py` pehli baar 15 skills pe chalaaya. Output mei multi-domain conflicts mili — `governed-publishing-discipline` aur `governed-content-publishing` dono "publishing/governance" domain mei. Consolidation candidate. `route.py` ne "why did traffic drop" ke liye `gsc-intelligence` ko top rank diya (trigger match + active health).


    Scaling lessons


    Jab 50+ skills ho jayengi, manual metadata impossible hai. Isliye mandatory 16 fields frontmatter mei — `registry_scan` automate kar leta hai. New skill add karte hi metadata bharo, warna router usse ignore karega (health_status default inactive).


    Why this is infrastructure, not optional


    Autonomous mesh (3 nodes) mei har node alag skills chala raha tha. Ek task pe inconsistent responses. Router ne standardize kiya — har node same logic. Is bina, distributed agent chaos hai.


    *Infra note. Not trading/investment advice.*



    Final recommendation

    Agar tumhare paas 10+ skills hain, aaj hi `registry_scan` banao. Conflicts visible honge. Ek primary rule enforce karo. 1 week mei agent ki clarity 10x ho jayegi.


    *Infra note. Not trading/investment advice.*



    Skill chaos silent killer hai. More skills = more confusion jab tak router na ho. 16 fields + 1 primary rule = scalable intelligence.



    *Infra note. Not trading/investment advice.*



    Build the router before you build the 50th skill. Order matters — chaos pehle aati hai, discipline baad mei nahi.



    *Infra note. Not trading/investment advice.*



    A well-routed skill library scales. A chaotic one collapses. Choose routing.



    *Infra note. Not trading/investment advice.*



    One more principle

    Router khud ek skill hai jo doosre skills ko route karta hai — isliye ise "meta-skill" kehte hain. Iska apna koi conclusion nahi hota, sirf routing. Ye separation of concerns hai: decision skills decide karein, router sirf assign kare.

    Educational only — not SEBI-registered investment advice. NISM-Series-XII certified; not a SEBI-registered Research Analyst. Content is educational only.

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